<<

BaselineBaseline Survey Survey of of Minority Minority Concentration Concentration : An Overview of the Findings Districts: An Overview of the Findings D. Narasimha Reddy*

I Introduction

It is universally recognized that promotion and protection of the rights of persons belonging to minorities contribute to the political and social stability of the countries in which they live. , a country with a long history and heritage, is known for its diversity in matters of religion, language and culture. ‘Unity in diversity’ is an oft-repeated characterization of India as well as a much-cherished aspiration, reflected in the constitutional commitment relating to the equality of citizens and the responsibility of the State to D.preserve, Narasimha protect and assure Reddy the rights of the minorities. Over the years, the process of development in the country did raise questions about the fair share of minorities, and point towards certain groups of them being left behind. “Despite the safeguard provided in the Constitution and the law in force, there persists among the minorities a feeling of inequality and discrimination. In order to preserve secular traditions and to promote National Integration, the Government of India attaches the highest importance to the enforcement of the safeguards provided for the minorities and is of firm view that effective institutional arrangements are urgently required for the enforcement and implementation of all the safeguards provided for the minorities in the Constitution, in the Central and State Laws and in the government policies and administrative schemes enunciated from time to time.” (MHA Resolution Notification No. II-16012/2/77 dated 12.01.1978). For * Visiting Professor, Institute for Human Development, New . The author is grateful to the ICSSR, for assigning him this task. Special thanks are due to the ChairmanIndian Prof. Javeed CouncilAlam and the then for Secretary Social Prof. T.C.A. Science Anant who took Researchkeen interest in the entire project on the survey of the MCDs and the follow up dissemination at the state level. Dr. Ranjit Sinha sustained the interest. This paper owes a great dealNew to Dr. DelhiSanchitta Dutta for her patient coordination and gentle persuasion in the successful completion of this work. Dr. Alakh Sharma with his optimism in getting all the data sorted out and Dr. Balwant with his skills of processing not so easy data, have been of great help at IHD, New Delhi. Still, it falls short of our own expectations for which the author alone is responsible. 1

The above cited resolution of the Ministry of Home Affairs paved the way for the establishment of a non-statutory ‘Minorities Commission’ in February 1978. As the years went by, the limitations of the non-statutory authority became evident and it was found wanting in effectively protecting the rights of the minorities. In May 1992, the National Commission on

Minorities (NCM) Act was passed and the NCM was established from May 1993 as an autonomous statutory body for the entire country except Jammu and Kashmir. The main functions of the NCM are to evaluate the progress of development of minorities in the Union and states, to monitor safeguards, to make recommendations for effective enforcement of these safeguards, to look into specific complaints regarding deprivation of rights, to initiate studies into problems of minorities etc. Under the NCM Act 1992, five minority communities were notified.

According to the Census 2001, the percentage of minorities in the country was about 18.4% of the total population, of which Muslims were 13.4%, Christians 2.3%, Sikhs 1.9%, Buddhists

0.8% and Zoroastrians (Parsis) 0.007%. “In six States the proportion of Muslims to total population is above the national average of 13.4% - (30.9%), (25.2%),

(24.6%), (18.55%), (16.5%) and (13.8%)”. A number of initiatives in the form of schemes and organizations have been initiated by the Union and the state governments to create conditions in which the minorities are assured their constitutional and legal rights and ensure that they are educationally and economically at par with the mainstream. Besides the NCM, these include the National Minorities Development and

Financial Corporation, the Prime Minister’s Fifteen Point Programme for the Welfare of

Minorities, and Minorities Commissions of some State governments.1 Notwithstanding these efforts, especially in the wake of India emerging as a fast growing economy, there has been a widely shared perception that of all the communities, Muslims lagged behind most. As one

1For a discussion of ‘Central Government Schemes and Commissions for Minorities’ see Khalidi (2006, pp. 229-240) and the Annual Reports of the Ministry of Minority Affairs, Government of India. 2 observer summed up, “Historians, politicians, journalists and others agree that Muslims in general lag behind other communities”. (Khalidi 2006, p. 1)

It is in this context that the Prime Minister’s High Level Committee (Sachar Committee) on the Social, Economic and Educational Status of the Muslim Community of India was set up in March 2005 with the main objective of assessing the social, economic and educational status of Muslims in the states, regions, districts and blocks that they live in, their livelihood activities, their levels of socio -economic development and their asset base and income levels relative to other groups. The Sachar Committee also looked into the issue of classification of certain

Muslim groups into ‘other backward classes’ (OBCs) and their share in total OBC population.

The Report of the Committee, submitted in 2006, has become a landmark in documenting the social, economic and educational status of Muslims, based on pooling together extensive information hitherto scattered across different sources. It exploded the myth that there was not adequate data for effectively assessing whether the development process in the country left behind certain communities. Beginning with the perceptions of the Muslim community on identity and security, which capture the pervasive feeling of insecurity, deprivation and discrimination, the Sachar Committee Report (SCR) focused on the issue of equity, and probed the question of whether different socio-economic categories in India have had an equal chance to reap the benefits of development. The main finding of the Report is that the Muslim community exhibited “deficits and deprivation in practically all dimensions of development” (p.

237). The SCR, based on several indicators made an assessment and different communities were placed on a scale of relative levels of socio-economic status. Except for a relatively lower infant mortality rate and better sex-ratio, Muslims rank by and large above Scheduled Castes (SCs) and

Scheduled Tribes (STs) but below the Hindu Other Backward Castes (OBCs). The SCR felt strongly that “policies to deal with the relative deprivation of the Muslims in the country should sharply focus on inclusive development and ‘mainstreaming’ of the community while respecting diversity”. The SCR made extensive suggestions and recommendations relating to general and

3 specific policy measures for key areas of intervention, touching upon a range of issues concerning affirmative action, access to credit, access to education, political representation and appropriate institutional arrangements, to overcome not only the deficits and deprivations but also to assuage the feeling among the Muslim community of being neglected.

Interestingly, while the SCR’s focus is on the socio-economic and educational status of the Muslim community, the overall approach suggested encompasses all minorities in their diversity, in the pursuit of inclusive development. “…The mechanisms to ensure equity and equality of opportunity to bring about inclusion should be such that diversity is achieved and at the same time the perception of discrimination is eliminated… This is only possible when the importance of Muslims as an intrinsic part of the diverse Indian social mosaic is squarely recognized” (SCR, p. 238).

Baseline Survey of Minority Concentration Districts

As a follow up to the recommendations of the SCR, the Union Ministry of Minority

Affairs initiated a number of measures, one of which is the identification and multisectoral development of minority concentration districts which suffer from deficits in terms of socio- economic aspects or in terms of basic amenities. The Minority Concentration Districts (MCD) project has two components: One is conducting of a baseline survey of the MCD districts, and the other is preparation and implementation of a multisectoral development plan in each of these districts. The baseline survey is conceived not only as a source of information on basic data for identifying gaps in socio-economic indicators and other specified amenities that would help in the design of multisectoral development plans for the MCDs, but also as the basis for monitoring the progress in overcoming the development deficits in these districts.

The task of conducting a baseline survey of MCDs is assigned to the Indian Council of

Social Science Research. Districts with Muslims, Sikhs, Christians, Buddhists and Parsis as minority concentrations are included by applying certain criteria. The Ministry of Minority

4

Affairs based the selection of MCDs on three criteria, viz.: the share of minority population, religion specific socio -economic indicators and indicators of basic amenities. The minority criterion required that a district has either a “substantial minority population of at least 25% of the total population or a large absolute minority population exceeding 5 lakhs but at least in the range of 20% to less than 25% of the total population or at least 15% of minority population, in case of six States / Union Territories where a minority community is in majority”. Thereafter, the positions of these districts were evaluated in terms of ‘backwardness’ against two sets of indicators, one relating to socio-economic aspects and the other relating to basic amenities. The four specific socio-economic indicators are: (i) literacy rate, (ii) female literacy rate, (iii) work participation rate and (iv) female work participation rate. The four indicators relating to basic amenities are: (i) percentage of households with pucca walls, (ii) percentage of households with safe drinking water, (iii) percentage of households with electricity and (iv) percentage of households with W/C latrines. Annexure A gives the indicators used for identification of MCDs and the distribution of MCDs across the States. Later, two more indicators relating to health were added. These are: (i). percentage of children vaccinated and (ii). percentage of institutional child deliveries. The Ministry has classified the districts with substantial minority population on the basis of religion specific socio -economic indicators and basic amenities indicators respectively into two broad groups: A total of 53 districts with both sets of indicators below the national average were considered more backward and were classified as group ‘A’ districts; and

37 districts with either of the indicator values below the national average were classified into group ‘B’. Group B was further classified into two sub-categories – B1 for which religion specific socio-economic indicators were below the national average, and B2 for which basic amenities indicators were below the national average. In all, 90 MCDs (53 A + 20 B1 + 17 B2) across 20 States and Union Territories were selected by the Ministry of Minority Affairs for the baseline survey. Annexure-B provides the State-wise distribution of A, B1and B2 category of

MCDs.

5

The baseline survey of the 90 MCDs was assigned to four ICSSR Social Science research institutions and two universities. The overall guidance was provided by an Expert Advisory

Group constituted for the purpose by the ICSSR. A systematic common methodology for the survey was designed and the survey was co nducted in the first half of 2008. Though there were a number of problems faced in the expeditious conduct of the studies, especially in the North-

East, because of the diverse weather and security conditions, all the study reports were completed by the middle of 2008. These reports, in spite of certain limitations to which we shall return later, have been a rich source material especially on the religion-specific in the socio- economic indicators and the overall basic amenities at the level of districts. These results were presented at dissemination workshops in the respective States, and have been of considerable help in designing multisectoral plans for the MCDs. Besides providing an information base for the multisectoral plans of the MCDs, the baseline survey reports are also aimed at serving as the basis for monitoring progress in reducing the imbalances during the Eleventh Five Year Plan.

In engaging with the task of monitoring the progress and assessing the extent of reduction or elimination of gaps during the Eleventh Plan, it would be useful to have an overview of the socio-economic conditions of different religious groups, and the access to certain basic amenities in these districts relative to the overall situation in the country as whole.

The reports of the baseline survey of the 90 MCDs have generated extensive data on the socio -economic status and access to basic amenities of minority communities as well as the others in these districts. The thrust of analysis of these reports are two-pronged:

a) Detailed gap analysis in terms of socio-economic indicators and the basic amenities in the

respective districts compared to the national averages. Based on the extent of the gap,

priority ranking is done for each of the ten indicators under the broad gro uping of socio-

economic indicators, basic amenities and health indicators.

b) Besides the gap analysis and priority ranking, the reports, based on the detailed village

and household level data, analyzed the situation in each of the districts in terms of not

6

only the socio -economic and amenities indicators but also the overall infrastructure

facilities, including social infrastructure like schools, health centres etc., and the reach of

various government programmes. The reports also make specific recommendations on

the nature of interventions needed at the district level.

The gap analysis and priority ranking have been found to be very useful inputs in the preparation of the multisectoral district plans for each of the 90 MCDs. The detailed analysis of district level conditions of living and access to basic amenities by the households of the minority and other communities, as well as of the infrastructure facilities, would be useful in designing specific interventions at the district level. However, individual district reports do not help in understanding the patterns in intra-community and inter-community differences at the regional or state level. Autonomy of policy making and administrative decision making still vests at the state level and is yet to percolate down to the district level. Regional or state patterns of intra- community and inter-community differences are very important in drawing lessons for intervention, for the simple reason that public administration patterns are seen more in terms of the state level, and the district level administration also largely reflects the administrative culture at the state level.

II Limitations of the Baseline Survey Reports for a Comparative Analysis over Time and Across Regions

In spite of efforts to follow a standardized methodology for the survey of all the 90

MCDs, there are differences in the resulting reports. Broadly there are three types of problems in analyzing these reports in a comparative perspective. First is the nature of conceptualization of the minority concentration. Second is in terms of the indicators used for inclusion and exclusion of the districts under MCDs. Third is in terms of the limitations of interpretation of concepts relating to data collection and differences in the presentation of the MCDs. Let us first examine the issue of nature of minorities included for the survey. The ‘baseline survey’ initiative is, as

7 mentioned earlier, the result of the Sachar Committee Report (SCR). The SCR brought out several blatant ‘development deficits’ of the Muslim community, and also pointed out the deficiencies in empirical data on socio -economic and basic amenities for decent living. The SCR was referring to the Muslim community alone as the deprived community. In contrast, the

Baseline Survey of MCDs, instead of confining the focus to the Muslim minority concentration districts, brought on board all minorities, as if all minorities did suffer deficits and should be treated equally. Many scholars have clearly pointed out that minority communities like Sikhs,

Parsis and Christians have been part of the mainstream (Shah, 2007) and if there were to be any indicators of discrimination, it would be proper to have a focused kind of survey of the regions where these minorities live. Instead, bringing in a category like ‘states where minorities are majority’ and picking up the districts with a certain percentage of the other communities, obfuscates the issue. For instance, in Jammu & Kashmir only Leh (Ladakh) could be picked up, but districts with similar deficits but inhabited by Muslims in the state do not get included in the baseline. Much weirder is the inclusion of four districts from , where the Buddhist minority community is predominantly made up of Buddhists with SC status. Similarly, the

Buddhist MCDs included in , Christian MCDs in , and Christians in Nicobar or in Wyanad are predominantly tribal communities. Further, inclusion of six districts from

Arunachal Pradesh, each with a population of less than one lakh scattered across the hills, makes any comparative analysis almost impossible. Therefore, the present overview is limited to a large extent to the Muslim MCDs.

Second, several of the indicators used in the ‘inclusion’ or ‘exclusion’ of districts are contestable.

For instance, higher work participation rate (WPR) or female work participation rate does not mean higher levels of development or vice versa. As pointed out by Dr. Kundu, “many of the developed districts and large urban centres report low WPR due to children and young adults being in educational institutions and elderly population’s affordability to withdraw from labour market. Poverty, illiteracy and survival strategy among deprived minority population would force

8 the households in less developed districts to send larger number of family members into labour market to eke out a living” (Kundu, 2008). Further, in almost all hill districts, female work participation is very high compared to the plains of Uttar Pradesh or Assam, West Bengal and even Bihar. These are determined by diverse socio -cultural factors. Similar is the definition in terms of ‘pucca walls’ for better housing. Often in regions like or Assam, the type of housing is dictated by the climatic and socio -cultural factors, and walls do not mean anything in terms of ‘development’.

The third limitation is due to the differences in the compilation of data and presentation of the results by MCD reports. In spite of clear guidelines and instructions, there are inter-institutional variations in the approach. In the case of at least two institutions, there are differences from report to report because of assigning work of some districts to some individual scholars and lack of coordination. One is not certain, for instance, how the concept of pucca walls is interpreted, or how ‘potable water connection’ is recorded in different reports! In many reports there is too much reliance on priority ranking of deficits without differentiating between capacity building variables like levels of education and variables which are the outcome of existing capacity like pucca housing (Hashim, 2008). Further, in spite of the well-known fact that Muslim minority communities derive much of their livelihood through household enterprises like tobacco, textiles, retail and wholesale trade, sale, repair and maintenance of motor vehicles, electrical machinery etc.; and most of them have their regional and local specificity, most of the reports routinely talk of secondary and service sector employment. There could at least be analysis of occupations at a two-digit level, which would be of immense help in designing local / region-specific financial, skill development and marketing interventions.

Fourth, some of the MCDs surveyed include less than 25% of minority community in the sample, for example Bulandshahar (13%), (15%), (19%) and (21%) in

U.P. Obviously the idea of ‘concentration’ is not kept in mind when it came to selection of villages in some MCDs. Notwithstanding these limitations, the Reports on MCDs do bring

9 together extensive data on several socio-economic variables and living conditions which help further analysis. As mentioned earlier, this overview paper attempts to make use of comparable data for different MCDs, with the objective of discerning certain patterns that may help better understanding of the socio-economic conditions and designing of appropriate interventions.

The baseline survey, as pointed out earlier, covered 90 MCDs spread over twenty states. The present analysis discusses these MCDs state-wise. The spread of the MCDs is thin across states, except in four states. Therefore, the focus of analysis in this overview is essentially on MCDs which are concentrated in Uttar Pradesh, Bihar, Assam and West Bengal.

III

The Approach

At the outset, it must be made clear that this overview does not summarize the findings of the MCD survey reports. The main objective of this overview paper is to examine whether these district level assessments help in discerning any patterns across the districts in terms of the indicators analyzed in the individual MCDs. Since the 90 MCDs are spread over as many as 20 states and the communities analyzed also vary across these states, a comparative analysis of intra- community and inter-community differences and similarities across the MCDs is done by confining to the state as a region. Though the analysis is presented state-wise, the focus is, as mentioned above, on the four major states viz. Uttar Pradesh, Bihar, West Bengal and Assam, which together account for 53 of the 90 MCDs. These are also the states where the minority community is predominantly Muslim, and these states together account for 56% of the total population of the Muslim community. True, the 90 MCDs include minority communities other than Muslims. The ‘minority concentration’ of these 90 districts varies widely. In the case of 62 districts, the minority refers to Muslims, in 14 MCDs it is Christians, in 13 it is Buddhists and in one case it is Sikhs. There is no district with a Parsi ‘concentration’. The basic difference is that most of these other minority communities included in MCDs live outside these districts, and

10 what is included of these communities in MCDs account for only a small fraction of them.

Analysis of their conditions in these specific MCDs thus does not help us much in knowing about these communities in general. For instance, by studying Christians in the N.C. Hills of

Assam, it is very difficult to come to any conclusion on the discrimination or ‘development’ of the Christian community elsewhere. An overwhelming majority of Christians, Buddhists and

Sikhs live in states and districts outside MCDs. But in the case of Muslims, an overwhelming majority live in the states from which the Muslim MCDs are drawn. Since, as observed earlier,

Christians, Buddhists, Sikhs and Parsis are considered part of the mainstream on par with the

Hindus-General, it would be very difficult to compare them with the major minority viz.

Muslims, and to draw any meaningful patterns that cut across these communities. Lastly, handling all the five minorities (since there is no Parsi MCD!) across thick (Muslim) and thin

(others) concentrations may turn out to be an unwieldy task, but state-wise analysis may yet capture the differentiation.

Among minority religions, though caste differentiation does not exist to the extent comparable to the , recognized intra-religious differentiation among Muslims, Christians and Sikhs do exist. The survey captures these differences more clearly among the Muslim minority districts than among Christian and Sikh MCDs. Though Islam as a religion is apparently egalitarian and has no place for a hierarchical caste structure, in reality the emergence of Islam as a carries the historical baggage of caste-class roots, and the pattern varies across the country. The Census of India, 1901 listed 133 social groups as wholly or partially Muslim. The widely perceived economic and educational backwardness of the Muslim community makes it necessary to take into consideration social stratification within the community for any meaningful intervention, including affirmative action. As observed by the

Sachar Committee Report (SCR 2006, p. 192), the present day Muslim society in India is divided into four major groups: (i). the Ashrafs who trace their origins to foreign lands such as Arabia,

Persia, Turkistan or Afghanistan; (ii). the upper caste Hindus who converted to Islam; (iii). the

11 middle caste converts whose occupations are ritually clean; and (iv). the converts from the erstwhile untouchable castes, bhangi (scavenger), mehta (sweeper), chamar (tanner), dom [M1]and so on. In terms of Muslim social hierarchy, these groups are placed into three categories viz.,

Ashraf, Ajlaf and Arzal. ‘Ashraf’ includes the first two categories mentioned above and could be called Muslim-General. ‘Ajlaf’ includes the third category and includes middle caste converts who are mostly artisans like carpenters, painters, milkmen, tanners etc. who could be compared to the Hindu OBCs. ‘Arzal’ includes the very low castes mentioned in the fourth category like chamar, bhangi etc. and could be equated with the Hindu SCs/STs.

Unlike the Hindu, Sikh and Buddhist religious groups, officially there si no recognition of

Scheduled Castes among the Muslim community. Muslims are divided into only two categories

Muslims-General and Muslim-OBCs. Muslims-General includes all groups referred to above as

‘Ashraf’. Muslim-OBCs include ‘Ajlaf’ as well as ‘Arzal’. One of the main findings of the Sachar

Committee Report (SCR, 2006) is that the Hindu-OBCs continue to be relatively deprived compared to Hindus-General, but the Muslim community as a whole is lagging behind Hindu-

OBCs. It is also observed that the condition of Muslim -OBCs is worse than that of the Muslim-

General. The SCR concludes that benefits of reservation are yet to reach most of the Muslim-

OBCs. Though there were two national and several State-level Commissions on ‘Backward

Classes’, the question of inclusion of certain groups under the OBC category, especially under

Muslim-OBC, is not a settled one (see for eg. Krishnan, 2010). However, even the existing grouping of Muslims into General and OBC does show certain clear regional patterns among the four major MCD concentration states viz. Uttar Pradesh, Bihar, West Bengal and Assam. Since the NSSO data of the recent rounds do provide the OBC category, there is as yet no state level disaggregation. The MCD survey reports are a substantial addition in filling the gap not only at the State level but also down to the district level, in the case of MCDs.

Table 1 shows that in U.P, Bihar, Kerala and Tamil Nadu, OBCs account for a major share of population, both among the Hindus and Muslims; whereas in West Bengal, Assam, and

12

Maharashtra, OBCs constitute a lower share among the Hindus and an insignificant proportion among Muslims. Muslims in West Bengal, Assam, Jammu & Kashmir and Maharashtra are overwhelmingly of the General category. Yet another distinguishing cultural difference among

Muslims between these states is the language. -speaking Muslims are concentrated in States like U.P. and Bihar (Khalidi, 2006, p. 2), while Muslims of Assam, West Bengal, Kerala and

Tamil Nadu speak mostly local languages like Assamese, Bengali, Malayalam and Tamil respectively. The basic question is to what extent these differences within the Muslim community in these states have a bearing on their living conditions? We shall now turn to each of the MCD states to analyze the inter-religious and intra-religious differences and similarities in a comparative perspective, in terms of education, occupation, assets, income, access to credit, indebtedness, access to amenities like housing, drinking water, sanitation and electricity.

Table1: Religious and Social Group Composition in Some of the Major Minority Concentration States

(% Distribution) State 2001 Hindus 2004-05 Muslims 2004-05 Hindus Muslims Others SC/ST OBC General OBCs General Uttar Pradesh 80.8 18.2 0.9 28.5 51.5 19.9 62.0 38.0 Bihar 79.6 15.9 0.2 26.9 60.2 12.8 63.4 36.6 Assam 64.9 30.9 4.2 40.7 26.6 33.8 3.0 97.0 West Bengal 72.5 25.2 2.3 42.0 8.4 49.6 2.4 97.6 Kerala 56.2 24.7 19.1 21.1 56.0 22.9 99.1 0.9 J &K 29.6 67.0 3.4 35.4 10.1 54.5 17.1 82.9 83.9 12.2 3.9 29.7 39.2 31.1 52.7 47.3 Maharashtra 80.4 10.6 9.0 22.2 37.7 40.1 11.6 88.4 Tamil Nadu 88.1 5.6 6.3 23.6 72.5 3.9 93.3 6.7 Punjab 36.9 1.6 61.5 39.6 14.3 46.1 54.4 45.6 India 80.5 13.4 6.1 31.2 43.0 25.9 40.7 59.3 Source: SCR (2006).

Map I shows the location of the MCDs. What is striking is that most of the MCDs are located at the inter-state or international borders. Besides the socio-economic and cultural dimensions, the spatially peripheral nature of these MCDs calls for special attention to their locational remoteness and specificities, and the consequent challenges to the delivery systems of programmes reaching these places and people. For the purpose of the overview analysis, the states are grouped into four broad regions viz. I. Northern States consisting of seven states viz.

Uttar Pradesh, Bihar, , Jharkhand, , Delhi and Jammu & Kashmir (J&K);

13

II. Eastern States consisting of three states viz. West Bengal, Assam and Orissa; III. North-

Eastern States consisting of Arunachal Pradesh, Manipur, , Mizoram and ; andIV. Other States consisting of six states viz. Maharashtra, Karnataka, Kerala, and Andaman and Nicobar Islands. Table 2 presents the region-wise distribution of MCDs. Of the twenty, as many as eight states have one MCD each, and in another four states, there are two

MCDs each. Thus, twelve out of twenty states account for only 16 MCDs, leaving 74 MCDs in eight states. Out of these eight states, the concentration is in four Northern and Eastern states

(Uttar Pradesh, Bihar, West Bengal and Assam) which account for 53 MCDs. The following sections present region/state-wise analysis of the important findings of the reports on MCDs.

Map 1: Minority Concentration Districts (MCDs)

14

Table 2: Region-wise Distribution of MCDs Regions / States No. of MCDs Regions / States No. of MCDs I. Northern States 38 III. North-East States 17 1. Uttar Pradesh 21 1. Arunachal Pradesh 7 2. Bihar 7 2. Manipur 6 3. Jharkhand 4 3. Meghalaya 1 4. Uttarakhand 2 4. Mizoram 2 5. Haryana 2 5. Sikkim 1 6. Jammu and Kashmir 1 IV. Other States 9 7. Delhi 1 1. Maharashtra 4 II. Eastern States 26 2. Madhya Pradesh 1 1. West Bengal 12 3. Karnataka 2 2. Assam 13 4. Kerala 1 3. Orissa 1 5. Andaman and Nicobar Islands 1 Total 90

IV

Northern States

The largest number of MCDs (38) are accounted for by the Northern region which consists of Uttar Pradesh (21), Bihar (7), Jharkhand (4), Uttarakhand (2),

Haryana (2), Jammu and Kashmir (1), and Delhi (1). The following is the analysis of the findings of the MCDs survey reports relating to these states.

4.1 Uttar Pradesh

Uttar Pradesh accounts for almost one fourth of the Muslim population in the country and of the 90 MCDs, the state accounts for 21, the highest number for any state. Further, all the

21 are Muslim minority districts. Uttar Pradesh, like the majority of Muslim minority concentration districts in the country, shows better sex ratio (Annexure 1). The survey results confirm that in MCDs as a whole, the sex ratio of the Muslim community (855) is higher than that of the Hindus (817). (Figure 1). The low level of the Muslim sex-ratio in J.P. Nagar is due to unusually low rate (557) among the Muslims-General. What is interesting is that overall sex-ratio among Muslims-General is lower than that of the Muslim-OBCs. The situation is quite the opposite in the case of Hindus-OBCs which is lower than not only the Hindus-General but also

SCs/ STs. There are four districts, Lakhimpur, Philibit, Badaun and Jyoti Phule Nagar where the sex-ratio of the minority community is less than that of the Hindus, but two out of them viz.,

15

Badaun and Jyoti Phule Nagar are the ones where the ratio is below 800 for both the Hindus and

Muslims.

Error! Reference source not found.

Literacy and Education

The baseline survey reveals some interesting facts about the current status of literacy in

MCDs in Uttar Pradesh, in contrast to earlier evidence. For the six and above age group, the average literacy levels for all the MCDs put together shows that it is higher for the Muslim community (43.3%) than the Hindus (35.5%) (Table 3). Also the range of literacy across the districts for Muslims is higher (32.2% to 56.8%) compared to the Hindus (23.7% to 49.8%)[M2].

The educational status of the minority (Muslim) community has been a persistent cause for concern and the survey of MCDs confirms that the minority deficits in education persist.

Though compared to the situation in 2001, the gap between the two communities in the levels of literacy declined, Table 2 shows that the difference is nowhere near disappearing. Figure 2 captures the gap and shows Barabanki (and Badaun) is the lowest performer for both the communities, and Rampur is the highest performer for both. In the case of elementary school dropouts at the primary level, they show marginally higher rates (5.25%) for Muslims than for the Hindus (3.23%) (Annexure 2). The dropout rates are high for both Hindus (7.12%) and

Muslims (15.20%) in . In the age group of 6-11 years, the ‘never enrolled’ account for 12.12% among Muslims compared to 7.39% among Hindus (Annexure 23).

Shahjahanpur, Badaun, Pilibhit and Shravasti account for very high levels of the ‘never enrolled’ category. Of course, the basic problem is apparently very poor levels of literacy, far below the national level, for both the communities, reflecting the extreme backwardness and the need for high priority interventions in the education sector.

The intervention in promoting education facilities should go beyond the primary level particularly for the Muslim community. Though their literacy levels compare well with the

16

Hindu community, when we turn to the proportion of literates with matriculation levels and above, the average for the minority community is as low as 6.7%, and it is more than double that for the Hindus, at 15.8% (Figure 3). In this regard, the differences between the lowest performing districts as also between the highest performing districts are also very high. The position of SC/ST communities is also higher (11.5%) than that of the Muslim community overall (67%) (Table 4). It is well known that cutting edge differences in education-based employment and earnings arise from the secondary and higher levels. The intervention needed is not only in terms of more schools but more secondary schools in the Muslim concentration areas, with support for the children to stay on and complete at least secondary levels of education. Another important factor, especially in the case of Muslim girl children, is the medium of instruction and the preference for Urdu. Urdu literacy in U.P. is now reported to be confined to young pupils schooled in the madrassas, or among older people above 70 (Khalidi,

2006). It is also observed that in 2002, there was “not a single government school in the entire state where Urdu is taught as a subject at any level” (Khalidi, 2006). There is extensive network of madrassa educational institutions which need considerable infusion of better quality training in

English, Mathematics and .

17

Table 3: Religious Composition of Population and Literacy in MCDs – U.P. District Population Share (%)* Literacy Rate (%) Hindu Muslim Hindu Muslim 59 41 64.28 65.28 Badaun 63 37 46.35 36.61 68 27 63.00 61.00 Lakhimpur 66 30 68.80 61.17 Muzaffar Nagar** 63 37 54.09 45.60 Pilibhit 70 21 68.53 63.22 J.P. Nagar 67 30 65.06 59.11 56 43 64.08 59.12 Barabanki 67 33 39.72 32.89 Bijnore 60 38 69.0 66.48 Shravasti 81 19 59.55 50.72 Lucknow 85 15 70.25 61.49 Rampur 45 52 78.00 70.00 Bulandshahar 87 13 75.31 65.35 70 25 50.60 39.70 Uttar Pradesh* 81 19 57.98 47.79 All India*** 81 13 65.10 59.10 *Rounded to the nearest integer **Some discrepancies in the data ***Census 2001

Figure 2: Literacy Rate Among Hindu and Muslim Communities in UP MCDs

100 Rampur, 78 80 State Average, Barabanki, 57.98 60 Rampur, 70 Hindu 39.77 40 Barabanki, State Average, Muslim 32.89 47.79

Literacy Rate 20 0 Lowest Average Highest UP MCDs

Error! Reference source not found. Table 4: District-wise Proportion of Matriculates and above in MCDs – U.P. (%) District Hindu Muslim SC/ST General OBC Total General OBC Total Siddharthnagar 7.3 28.2 7.4 11.4 8.6 3.3 5.3 Badaun 5.8 13.8 7.4 7.6 10.3 4.3 6.5 Bahraich 7.9 27.8 7.7 11.1 5.2 4.8 4.9 Lakhimpur 8.4 17.6 16.5 13.4 6.5 6.5 6.4 Muzaffar Nagar 11.1 19.0 13.4 12.5 5.5 3.9 4.3 Balrampur 5.9 36.0 8.5 13.6 13.0 3.8 5.0 Pilibhit 6.4 11.8 11.7 10.1 2.4 3.4 3.6 J.P. Nagar 13.8 29.6 16.6 16.0 23.1 12.6 13.8 Moradabad 8.6 23.9 11.8 12.2 5.6 6.9 6.5 Saharanpur 20.8 28.7 26.4 24.6 33.3 10.3 10.5 Barabanki 7.4 31.5 18.1 15.2 4.3 3.9 3.9 Bijnore 14.3 33.0 19.5 17.9 7.9 7.3 7.5 Baghpat 20.2 37.6 30.6 28.8 25.0 10.0 10.1 Shravasti 5.9 21.9 8.4 9.9 2.4 3.3 3.3 Lucknow 12.2 36.4 16.6 17.9 14.3 4.9 4.9 Bareilly 15.5 29.5 17.3 17.9 8.8 8.9 8.3 Rampur 14.4 27.4 18.2 17.0 0.0 8.9 8.9 Bulandshahar 21.7 40.0 30.5 30.0 8.8 11.7 11.0 Shahjahanpur 5.1 12.9 7.9 7.7 10.3 2.4 3.7 Average 11.5 28.4 15.4 15.8 8.2 6.4 6.7

18

Occupational Pattern, Assets and Income

Though the majority of both the Hindu and Muslim communities live in rural areas in

Uttar Pradesh, landlessness as revealed by the survey reports of the MCDs is much higher among Muslim community (46.4%) compared to the Hindus (29.38%) (Table 5). Landlessness among the Muslim community is higher than even that of the SCs, and in certain districts, it is as high as 95.40% in Baghapat, 81.84% in Muzzafarnagar and 78.55% in Bijnore. In contrast, almost all Hindu and Muslim households appear to have access to land in J.P. Nagar. As a consequence, though they live in rural areas, agriculture and allied activities constitute a much lower source (42.5%) of employment or livelihood for Muslims in the MCDs, compared to that of (59.5%) the Hindus (Table 6). A large number of workers are forced to migrate or commute for work in non-agricultural activities. The employment condition is bad for all, but it is worse for the landless Muslims. There are exceptions where a majority of the Muslim workforce is in agriculture like in Rampur (66.6%), Shravasti (63.6%), Moradabad (55.1%) and Lakhimpur

(49.9%). Wherever the majority of the Muslims are in agriculture, it is the Muslim-General community that has higher share in agriculture than the Muslim-OBCs. There are also wide inter-district variations. In Rampur and Shravasti, both Hindu and Muslim communities have a majority of households in agriculture, whereas in Bhagapat, both Hindus and Muslims have a lower share in agricultural occupations. Barring these exceptions, the major source of livelihood for the Muslim community is petty production, construction, trade, repairs and other services.

In U.P. and Bihar, and in Northern India in general, historically the groups who moved into

Islam ‘were mainly artisans and artisanal castes’ and other “occupational castes – occupational as understood in India, i.e., excluding those engaged in agriculture” (Krishnan, 2010). The secondary sector as a whole provides employment to the extent of 43.3%, and the services account for 14.2% of employment of the Muslim community (Table 7). Of the 21 MCDs, there are six districts viz. Baghapat (74.9%), Badaun (64.7%), Shaharanpur (58.5%), Bijnore (58%),

Muzzafarnagr (53.2%) and Pilibhit (50.8%) where the majority of the Muslim workers are in the

19

secondary sector. The proportion of Muslim-OBCs depending on the secondary sector is higher

than that of the Muslims-General. It is not surprising that Muslim-OBCs are identified on the

basis of their traditional occupation (SCR 2006, p. 192).

Table 5: Proportion of Landless Households in U.P. MCDs (%) District Hindu Muslim SC/ST General OBC Total General OBC Total

Siddharthnagar 36.14 23.58 16.49 23.77 23.08 30.23 28.08 Badaun 46.15 23.60 26.80 36.03 39.81 50.24 45.92 Bahraich 24.29 6.90 16.71 17.51 31.25 33.52 33.85 Lakhimpur 17.60 5.56 9.78 12.35 31.07 32.92 31.95 Muzaffar Nagar 78.85 22.45 54.22 65.84 51.16 85.37 81.84 Balrampur 20.42 10.81 17.05 16.96 11.11 30.85 28.44 Pilibhit 42.59 25.00 27.06 32.27 76.00 62.02 65.79 J.P. Nagar 1.58 4.76 0.00 1.12 0.00 0.87 0.76 Moradabad 46.61 13.89 21.55 30.00 41.67 31.65 34.74 Fig 3B:Saharanpur Landlessness Among Hindu61.07 Social Groups29.29 in UP33.33 MCDs 44.21 100.00 64.33 65.97 Barabanki 15.36 10.94 12.18 13.46 57.14 39.93 41.41 90 Bijnore 63.26 23.08 46.31 53.51 53.33 79.64 78.55 83.51, Baghpat 80 Baghpat 83.51 30.51 39.94 50.85 100.00 95.22 95.40 Shravasti 18.03 9.18 11.23 12.82 33.33 33.62 33.33 % of Landless Households 70 Lucknow 42.28 28.68 43.37 40.21 100.00 55.32 55.10 Bareilly 33.87 11.11 19.58 23.14 27.59 54.24 46.04 54.22, Muzzafarnagar 60 Rampur 20.67 14.29 11.98 15.85 0.00 24.78 24.59 Bulandshahar 42.73 30.06 30.67 34.34 62.50 48.70 51.96 50 SC/ST Shahjahanpur 39.42 25.00 26.00 30.96 OBC55.56 58.60 58.33 Average 39.78 20.04 23.11 29.38 37.72 47.81 46.41 40 39.78 Hindu-General

30 30.5, Baghpat 23.11 20 20.04 Fig. 3A: Landlessness Among Hindus and Muslims in UP MCDs

120 95.4, Baghapat 100 10 80 4.76, J.P. Nagar 60 46.41 40 65.84, 1.58, JP Nagar 29.38 Muzzafarnagar 0 20 0.76, J.P.Nagar 0, J.P. Nagar 0 1.12, J.P. Nagar Lowest Average % of Households without Land Lowest HighestAverage Highest Hindu Muslim

Error! Reference source not found.

Fig 3C: Landlessness Among Muslim Social Groups in UP MCDs

120 100, Baghpat/ Lucknow/ 100 Saharanpur

80 95.4, Baghpat

60 47.81 40 37.72 20 0, JP Nagar % of Households without Land 0 0.87, JP Nagar Lowest Average Highest Muslim OBC Muslim General

Table 6: Agriculture & Allied Employm ent in U.P. MCDs District Hindu Muslim SC/ST General OBC Total General OBC Total

20

Siddharthnagar 34.8 42.7 52.0 45.3 45.8 29.3 35.7 Badaun 30.5 66.4 56.8 45.2 33.7 28.9 31.0 Bahraich 59.1 68.3 61.5 61.8 42.7 41.8 41.3 Lakhimpur 61.8 82.3 74.5 70.6 55.2 46.6 49.9 Muzaffar Nagar 39.6 73.5 55.2 47.1 52.4 33.6 35.6 Balrampur 52.7 63.6 58.0 57.3 62.4 43.0 45.4 Pilibhit 70.1 73.3 70.3 70.4 21.8 48.8 40.8 J.P. Nagar 48.8 50.0 59.0 53.1 51.8 41.7 42.4 Moradabad 49.1 72.9 72.9 64.5 42.3 58.0 55.1 Saharanpur 35.6 63.7 61.1 51.4 26.8 26.7 Barabanki 64.3 65.0 69.6 66.8 26.3 38.0 36.6 Bijnore 51.9 67.5 59.3 55.7 35.3 32.0 32.1 Baghpat 17.2 60.8 56.4 45.6 20.0 11.7 11.5 Shravasti 68.1 75.0 73.3 72.2 83.3 62.5 63.6 Lucknow 49.0 50.5 49.8 49.5 50.0 26.0 26.8 Bareilly 40.4 64.0 57.1 52.9 44.0 27.8 35.7 Rampur 73.5 75.9 81.4 77.6 100.0 65.9 66.6 Bulandshahar 53.5 72.8 68.7 64.9 30.9 53.6 48.1 Shahjahanpur 61.2 67.2 69.6 66.1 32.2 33.3 34.9 Average 51.0 66.1 64.6 59.5 43.8 42.2 42.5

Table 6A: Employment of Hindu and Muslim Communities in the Agricultural Sector in U.P. MCDs Caste/Community % of Employment in Agriculture Average for UP MCDs Lowest / District Highest / District Hindu-General 66.1 42.7 82.3 (Siddardhanagar Lakhimpur) Hindu-OBC 64.6 49.8 74.5 (Lucknow) (Lakhimpur) Hindu-SC/ST 51.0 17.2 73.5 (Baghpat) (Rampur) Muslim -General 43.8 20.0 100.0 (Baghpat) (Rampur) Muslim -OBC 42.2 11.7 65.9 (Baghpat) (Rampur)

Table 7: Secondary Sector Employment in U.P. MCDs District Hindu Muslim SC/ST General OBC Total General OBC Total

Siddharthnagar 56.7 30.8 37.5 41.9 34.4 55.9 47.4 Badaun 66.3 29.8 40.8 51.8 61.1 67.1 64.7 Bahraich 33.4 10.9 28.3 27.2 42.7 40.9 42.2 Lakhimpur 30.7 8.6 15.5 20.6 30.5 36.2 34.2 Muzaffar Nagar 52.6 10.8 32.4 43.1 42.7 53.7 53.2 Balrampur 39.2 11.1 34.0 31.4 7.1 38.0 34.2 Pilibhit 26.5 10.7 22.3 22.8 63.2 45.6 50.8 J.P. Nagar 47.5 32.1 38.1 42.7 10.7 45.2 42.2 Moradabad 44.1 16.1 21.4 28.7 52.6 35.4 38.9 Saharanpur 16.5 6.9 5.5 10.3 NA 11.3 10.0 Barabanki 28.0 14.6 21.7 23.7 54.4 51.5 51.7 Bijnore 42.4 10.8 31.9 36.0 52.9 58.2 58.0 Baghpat 64.9 11.6 27.0 35.4 20.0 76.1 74.9 Shravasti 23.3 8.5 16.4 17.1 13.9 22.5 22.0 Lucknow 36.0 18.5 28.9 31.1 0.0 34.1 33.6 Bareilly 49.7 24.7 32.0 36.5 40.5 57.4 49.2 Rampur 23.6 17.2 17.2 20.1 0.0 25.3 24.7 Bulandshahar 40.4 13.8 23.5 26.3 68.3 39.6 46.6 Shahjahanpur 33.7 24.1 25.2 28.3 54.2 61.2 58.5 Average 39.5 15.3 25.5 29.5 42.2 43.7 43.3 Table 8: Employment of Hindu and Muslim Communities in the Secondary Sector in U.P. MCDs Caste/Community % of Employment in Secondary Sector Average for MCDs Lowest / District Highest / District Hindu-General 15.3 8.6 32.1

21

(Lakhimpur) (J.P. Nagar) Hindu-OBC 25.5 5.5 40.8 (Saharanpur) (Badaun) Hindu-SC/ST 39.5 16.5 66.3 (Saharanpur) (Badaun) Muslim -General 42.2 0.0 68.3 (Rampur / Lucknow) (Bulandsahar) Muslim -OBC 43.7 11.3 76.1 (Saharanpur) (Baghpat)

Table 9: Employment in Tertiary Sector Across Communities in U.P. MCDs Caste / Community % of Employment in the Tertiary Sector Average for UP MCDs Lowest / District Highest / District Hindu – General 18.7 3.8 31.0 (Badaun) (Lucknow) Hindu – OBC 9.9 1.5 33.4 (Rampur) (Saharanpur) Hindu – SC/ST 9.5 2.9 47.9 (Rampur) (Saharanpur) Muslim – General 14.0 0.8 60.0 (Bulandshah) (Baghpat) Muslim – OBC 14.0 4.1 39.9 (Badaun) (Lucknow)

Though non-agricultural activities constitute the major source of employment to the

Muslim community, much of it is in the nature of self-employment and own account enterprises,

often home-based activities, that involve women and family labour. Most of these traditional

occupations are of low productivity and require considerable state support in upgrading

technology and re-skilling. Employment in the tertiary sector is an extremely mixed bag of jobs

ranging from personal or petty services to commercial and government services. The type of

jobs from a sweeper or attender to that of a clerk or teacher may also have considerable caste /

community baggage. Annexure 4 shows that overall for the Hindu community, services account

for only 11%, and they account for 14% for Muslims. There are inter-caste differences among

Hindus, and not much difference in overall share among Muslims, as shown in Table 9. But the

quality of jobs is bound to be different across castes and communities, which are difficult to

discern from these aggregate figures.

The MCDs in U.P. show that average size of the family of the minority community is

larger (6.6) compared to the Hindus (5.9), and the difference persists across all MCDs (Figure 4).

Annexure 5 provides caste / community-wise details for all U.P. MCDs. The proportion of

dependants on the workers in a household (dependency ratio) is also higher among the Muslims

22

(94.6%) compared to the Hindus (82.3%) (Annexure 6). The dependency ratio, besides caste / community variation also has a clear regional dimension as well (Figure 5). The larger family size and higher dependency ratio weighs against the Muslim community’s living standards.

Figure 4: Family Size Across Communities in UP MCDs

10 Balarampur, 7.9 Shajahanpur, 8 6.1 6.6 6 5.9 Lakhimpur, 7.1 4 Barabanki, 5.1

Family Size 2 0 Smallest Average Largest MCDs of UP Hindu Muslim

Figure 5: Dependency Ratio in Across Communities in UP MCDs

Shravasti, 140 121.2 120 94.6 Rampur, 72.7 100 80 60 82.3 Shravasti, 98.9 40 Rampur, 64.6 20 Dependency Ratio 0 Lowest Average Highest Hindu Muslim

‘Dependency Ratio’ = Percentage of dependent population to working population

In the MCDs of U.P. there are certain interesting aspects of occupational activities and dependence on multiple sources of income among both Hindu and Muslim communities. For many Muslim households, ‘animal husbandry’ including dairy, poultry and goat rearing has been an important source of income. When asked about preference for additional sources of income, both Muslim and Hindu households gave top preference for to ‘animal husbandry’ in

Moradabad, Rampur, Badaun, Bahraich, Balarampur, Shravasti and Shahjahanpur.

The other important source of employment is construction. Next to agriculture, construction is the second main source of employment for both Hindu and Muslim communities in Bahraich, Balarampur, and Siddharthanagar. Similarly, manufacturing is the second most important occupation in Badaun, Moradabad, Shahjahanpur, Barabanki and Bijnore. These occupation and region specificities require designing of facilities for training in skills and capabilities in organization, production and marketing. Financial support is yet another factor that is likely to enable artisans to emerge as entrepreneurs. But at present most of these artisans

23 languish in semi-bondage conditions particularly in the metal industry, chikan (embroidery), carpet-making, furniture-making and similar trades.

Indebtedness and Sources of Credit

Substantial dependence on self-employment is linked to the need for regular, though relatively small, investment. Availability of institutional credit at fair rates of interest becomes an important requirement for small trade, business or production activities. The survey reports of the MCDs in U.P show that in terms of incidence of household indebtedness there is little variation across communities, as shown in Annexure 7. It is actually less for the Muslim community (31.3%) compared to the Hindus (34.7%), and it is difficult to say from the data how much of it is due to lack of a proper supply of credit. However, lower incidence of indebtedness does not necessarily mean a better situation. On the contrary, it may mean lack of credit-worthiness or fear of indebtedness – both of which can act as constraints for any improvement in earning capacity, self-employment, or own account activities, which are the main sources of livelihood. The survey results show that though indebtedness of Muslim households is low, the share of institutional sources like banks and cooperatives in their borrowings is much lower. Institutional sources account for only 23.75% of borrowings of Muslims across the

MCDs, while it is 39.33% for the Hindus. Annexure 8 brings out clearly the caste / community dimensions of the share of institutional credit in the household indebtedness. Hindus-General have the highest share (49.03%), followed by Hindu-OBCs (41.66%), Hindu-SCs/STs (33.65%),

Muslims-General (31.18%) and Muslim-OBCs (21.71%). Further, Figures 6 and 7 bring out the clear regional dimension as well. The best performance of Rampur, regardless of caste / community, stands out. In Balarampur, the share is as high as 70.97% for Muslims and 50% for the Hindus, while in Rampur it is 65.79% for Muslims and 77.14% for the Hindus. Could these districts serve as examples for any institutional initiatives on improving formal credit, to the poor in general and especially to the Muslims? In both their cases, institutional credit is very low,

24 forcing them to depend on high interest bearing sources like moneylenders and traders, but it is worse in the case of the Muslims. The situation varies across these MCDs. The share of institutional sources is less than 10% for both Hindus and Muslims in Baghapat and

Muzaffarnagar, 10% to 20% in another seven districts for Muslims, but somewhat higher, though still only about one-third, for the Hindus.

Figure 6: Institutional (Formal) Sources of Indebtedness in UP MCDs

120 Rampur 100 100 Rampur 80 85.9 SC/ST 49.03 60 Bijnore Bijnore Hindu-OBC 25 41.66 75 Hindu-General 40 Sahanpur 33.65 20 20.2 Baghpt 0 9.86 Institutional Credi as % of Total Lowest Average Highest

Figure 7: Institutional (Formal) Sources of Indebtedness in UP MCDs - Muslim: General and OBC

120 Balarampur,100 100

80

60

Debt Rampur, 66.6 31.18 40 Bareily , 17.39 20 21.71 Siddarathnagar, 0 6.15 Institutional Sources as % of Total Lowest Average Highest Muslim-General Muslim-OBC

Access to Basic Amenities

Except access to drinking water, the overall situation relating to other amenities, like houses with pucca walls, electricity connections and W.C. toilets, in most of the MCDs is dismal.

Though it is less than the national average of 87.90%, overall 76.07% of Muslim households and

72.25% of Hindu households have access to safe drinking water. But here again there is a certain caste hierarchy. 79.77% of Hindus-General, 77.73% of Hindu-OBCs and only 63.42% of

SCs/STs have access to safe drinking water (Annexure 9). It is similar in the case of the minority community, with Muslims-General and Muslim-OBCs having 81.75% and 74.85% accessibility respectively. In the case of housing, hardly one-third of the households have houses with pucca walls, though the Hindus are marginally better with 36.27% compared to the Muslims with

30.95%. Annexure 10 shows that there is hardly any district, except Bulandshahar, where access to pucca housing is anywhere near the national average of about 59%. However, there is a clear caste/ community difference with 48.90% of Hindus-General, 36.26% of Hindu-OBCs, 32.54%

25 of SCs/STs, 37.68% of Muslims-General and only 29.83% of Muslim-OBCs having housing with pucca walls (Table 10). Regionally, Rampur, Bulandshahar and Saharanpur do much better, while Lucknow and Lakhimpur are dismal. The situation relating to in-house W.C. toilets is worse, but Muslims are slightly better off with 31.16% compared to 20.55% for the Hindus

(Annexure 11). But here again there is clear caste difference among both Hindus and Muslims

(Table 11). Rampur and Sahranpur show very high levels of houses with W.C. toilets but

Siddharthanagar, Shravasti and Barabanki languish. The worst scenario with regard to basic amenities is regarding provision of electricity connections to residential houses. Less than one- fourth of the households, 21.3% Muslim and 24.3% Hindu, have electricity connections

(Annexure 12). As in housing, drinking water and sanitation, there is a clear caste hierarchy of access even in the case of electricity, among both Hindu and Muslim households (Table 12). In four districts, Bahraich, Lakhimpur, J.P. Nagar and Shravasti, about 90% or more of both Hindu and Muslim households do not have electricity connections. In nine out of 21 districts, less than

10% of SC/ST households have power connections. Overall the amenities situation in the

MCDs of U.P. shows the dismal failure of the State.

Table 10: Caste /Community-wise Access to Pucca Housing in U.P. MCDs Caste / Community % of Households with Pucca Houses Average for UP MCDs Lowest / District Highest / District Hindu – General 48.90 14.06 78.57 (Lucknow) (Rampur) Hindu – OBC 36.26 15.38 74.00 (Lucknow) (Bulandshah) Hindu – SC/ST 32.54 15.75 70.00 (Lucknow) (Bulandshah) Muslim – General 37.68 13.73 100.00 (Lakhimpur) (Saharanpur0 Muslim – OBC 29.83 14.73 62.99 (Lakhimpur) (Bulandshah)

Table 11: Caste /Community-wise Access to W.C. Toilet Facility in U.P. MCDs Caste / Community % of Households with W.C. Toilet Facility Average for UP MCDs Lowest / District Highest / District Hindu – General 29.58 12.26 71.43 (Siddharthanagar) (Rampur) Hindu – OBC 20.95 1.79 66.36 (Siddharthanagar) (Rampur) Hindu – SC/ST 16.91 5.24 62.57 (Barabanki) (Rampur) Muslim – General 35.78 11.11 100.0 (Shravasti) (Saharanpur) Muslim – OBC 30.10 3.40 71.18 (Shravasti) (Rampur)

26

Table 12: Caste/ Community-wise Electricity Connections in U.P. MCDs Caste / Community % of Households with Electricity Average for UP MCDs Lowest / District Highest / District Hindu – General 35.8 7.1 76.1 (J.P. Nagar) (Baghpat) Hindu – OBC 25.2 5.8 78.1 (Bahraich) (Saharanpur) Hindu – SC/ST 19.1 4.9 72.8 (Shravasti) (Saharanpur) Muslim – General 22.2 7.1 100.0 (J.P. Nagar) (Saharanpur) Muslim – OBC 20.8 4.0 64.1 (Bahraich) (Saharanpur)

Table 13: Access to PDS Across Communities in U.P. MCDs Caste / Community % of Households Accessing PDS Average for UP MCDs Lowest / District Highest / District Hindu – General 31.70 5.26 100.0 (Bulandshahar) (Rampur) Hindu – OBC 28.25 3.73 71.43 (J.P. Nagar) (Rampur) Hindu – SC/ST 26.76 2.84 80.95 (Bulandshahar) (Rampur) Muslim – General 26.96 6.25 100.0 (Bulandshahar) (Lucknow / Sharanpur) Muslim – OBC 31.85 2.67 76.82 (Bulandshahar) (Rampur)

Public Distribution System (PDS)

The Public Distribution System seems to be at a low level, although Muslims have a marginal edge in accessing it (31%) compared to Hindus (28%) (Annexure 13). But even here, there are some better performing districts which may hold lessons. For instance in Rampur, 77% of the Hindu households and 76% of Muslim households access PDS. In Barabanki it is 50% access for Hindus and 56% for Muslims, but, is 4% for all in Bulandshahar. What accounts for such a vast difference within a State and within the sub -group of MCDs is a big puzzle.

4.2 Bihar

Bihar, with about 13% of the total Muslim population of the country, has the third largest concentration of the community. All the seven MCDs from the state belong to the ‘A’ category, implying that these districts suffer from deficits cutting across both socio -economic and basic amenities indicators. MCDs in Bihar too, show that in terms of sex-ratio, the Muslim community is better placed with 894 compared to 862 of the Hindu community. And among both Hindu and Muslim communities, sex ratio is higher in the ‘General’ category than others.

27

Table 14: District-wise Sex Ratio - Bihar Hindu Muslim SC & District ST OBC GC* All OBC GC* All Araria 810 919 947 875 876 973 910 Bettiah 784 882 931 843 880 934 896 Darbhanga 839 853 896 851 867 874 871 Katihar 918 865 824 881 872 898 886 Kishanganj 889 865 800 874 947 905 924 Purniya 844 822 1016 844 817 941 841 Sitamari 988 827 867 878 884 982 935 Average 856 860 904 862 877 918 894 *GC: General category

Literacy and Education

In the case of literacy, the overall level in Bihar is much lower than the national average.

In Bihar MCDs, literacy rate of the Hindus is marginally higher at 57.68% co mpared to the

Muslims at 55.8% (Annexure 14). There does not seem to be any reflecting[M3] in literacy levels in either Hindu or Muslim communities. Table 15 shows Hindus-General at a much higher level than the OBCs, and below that is the literacy level of SCs/STs. The Muslim-General literacy rate is marginally lower than that of Hindu-OBCs and more than Muslim-OBCs. Purniya stands out as a poor performer for both the communities, though Hindus are slightly better off at

49.5% compared to Muslims at 44.82% . The caste divide is at the beginning of the education process. Annexure 16 gives detailed data on caste/community-wise enrolment rates among the

5-15 age group. The enrolment rate of Hindus-General is higher (91.10%) than the Hindu-

OBCs (82.62%) and the latter is higher than SCs/STs (75.58%) (Table 16). The Muslim-General enrolment rate is less (80.60%) than Hindu-OBCs but more than Muslim-OBCs (76.38%). Even in enrolments, Purniya district is comprehensively at the bottom, in contrast to Araria which is on top. In the case of the ‘never enrolled’ category, a very high level is a cause for concern for both the communities though Hindus are marginally better, but caste hierarchy is reflected here too (Table 17). The dropout rate for those in the 5-15 age group is also marginally less for

Hindus at 2.43% against 3.06% for the Muslims (Annexure 15). But the real difference is seen in the case of those with education levels of ‘matriculation and above’, with the Hindu community

28 at 14.10% and the Muslim 9.69% (Annexure 17). It is well known that if education is to make a difference, one must attain at least matriculation level. It is at this level the gap between communities widens and results in permanent differentiation. Table 18 shows that at the

‘m atriculation and above’ level, there is a wide gap in both Hindu-Muslim differences and intra- community differences. The Hindus-General at this level are more than three times the

Muslims-General, two times the Hindu-OBCs and almost four times the SCs/STs. Reducing this gap needs substantial state initiative and investment. Privatization in the arena of higher education would only worsen the situation. Though both are lower, f[M4]ocus on secondary school facilities with retention incentives are needed in a more focused way for the minority community. What makes Darbhanga different in terms of better educational performance?

29

Table 15: Caste/Community-wise Literacy in Bihar MCDs (%) Caste / Community Literacy Rate for 6 years and above in Bihar MCDs Average for MCDs Lowest / District Highest / District Hindu – General 78.82 54.37 83.79 (Purniya) (Sitamari) Hindu – OBC 60.00 55.89 67.36 (Purniya) (Kishanganj) Hindu – SC/ST 49.34 38.36 53.56 (Purniya) (Katihar) Muslim – General 59.09 51.25 72.46 (Purniya) (Bettiah) Muslim – OBC 54.10 43.56 61.75 (Purniya) (Bettiah)

Table 16: Caste/ Community-wise Enrolment Rate Among 5-15 Age Group in Bihar MCDs Caste / Community Enrolment Rate % Average for MCDs Lowest / District Highest / District Hindu – General 91.0 85.29 100.00 (Purniya) (Araria, Katihar, Kishanganj) Hindu – OBC 82.62 78.40 90.39 (Kishanganj) (Araria) Hindu – SC/ST 75.58 65.75 86.09 (Purniya) (Araria) Muslim – General 80.60 71.75 96.03 (Purniya) (Araria) Muslim – OBC 76.38 62.71 90.69 (Purniya) (Araria)

Table 17: District-wise ‘Never Enrolled’ in Bihar MCDs (%) Muslim Hindu District SC & OBC ST OBC GC* Total GC* Total Araria 10.60 3.06 0.00 5.78 5.80 1.59 4.98 Bettiah 23.94 15.72 6.31 18.35 22.90 17.37 20.59 Darbhanga 30.63 15.93 7.02 21.75 23.40 15.82 19.18 Katihar 10.87 11.52 0.00 11.11 16.23 12.22 13.97 Kishanganj 21.99 17.84 0.00 19.27 19.80 21.10 20.35 Purniya 34.25 19.11 11.76 23.71 35.97 28.25 34.68 Sitamari 22.96 15.85 10.62 17.36 20.95 11.18 16.40 Average 22.94 14.08 8.47 16.91 21.02 15.63 18.98 *GC: General category

Table 18: Caste/ Community-wise ‘Matric and Above’ in Bihar MCDs Caste / Community % of those with ‘Matric and Above’ Average for MCDs Lowest / District Highest / District Hindu – General 32.13 11.11 37.14 (Kishanganj) (Dharbhanga) Hindu – OBC 13.37 6.12 20.79 (Kishanganj) (Araria) Hindu – SC/ST 8.67 4.30 12.18 (Kishanganj) (Dharbhanga) Muslim – General 10.59 7.17 15.09 (Araria) (Bettiah) Muslim – OBC 9.12 5.91 10.83 (Bettiah) (Purniya)

Occupational Pattern, Assets and Income

One common factor in the Muslim and Hindu differentiation that appears to cut across states and districts is the size of the family and the ‘dependency ratio’. Like in U.P., in Bihar

30

MCDs too the average size of the families of the minority community is larger (6.0) than that of the Hindus (5.6) (Annexure 18). Dependency ratio, seen as the percentage of dependents to working members in a household, is very high for both the communities, but worse for Muslims

(100%) than Hindus (91.1%) (Annexure 19). Table 19 shows that the lower the position in caste hierarchy, the higher is the dependency rate. The spectrum of dependency with the lowest level for Hindus-General (70%) and the highest for Muslim-OBCs reflects the caste hierarchy. The family size seems to be seen as an asset where there is heavy reliance on self-employment and family-based own account work for livelihood, which is more so in the case of Muslims.

Table 19: Caste/ Community-wise Dependency Rate in Bihar MCDs Caste / Community Dependency Rate % Average for MCDs Lowest / District Highest / District Hindu – General 70.0 50.0 90.0 (Kishanganj) (Araria) Hindu – OBC 91.0 87.0 96.0 (Purniya/Bettiah) (Katihar) Hindu – SC/ST 97.0 91.0 113.0 (Darbhangha) (Sitamari) Muslim – General 94.0 83.0 107.0 (Araria) (Bettiah) Muslim – OBC 105.0 102.0 113.0 (Araria, ..) (Katihar)

‘Bihar Paradox’

We have noticed that landlessness is more among Muslims in Uttar Pradesh, and it is expected to be so in many other parts of the country. But this is not the case in Bihar.

Landlessness in rural Bihar is at a shockingly high level for both the communities. Perhaps Bihar is a unique case where overall landlessness is not only high but it is higher for the Hindu community (63.78%) as a whole than for the Muslims (62.72%), as shown by the MCD survey data (Table 20). Here again, caste and community hierarchy are mirrored in the access to land.

Landlessness is relatively low among Hindus-General (39.55%) compared to Hindu-OBCs

(55.95%) and SCs/STs (79.92%). Similarly, landlessness among Muslims-General is less

(57.16%) than Muslim-OBCs (65.94%). This has serious implications for the state and the districts which are essentially rural in nature, and where the main source of livelihood is agriculture. In Bihar too there are intra-community and inter-community differences in

31 occupational pattern. While the landless Hindus seem to depend more on agricultural labour, the landless Muslims, besides agriculture, depend a little more on non-agricultural production.

While 65.72% of working Hindus are in agriculture, Muslim dependence on agriculture at

54.09%, though high, is much less compared to the Hindus (Table 21).

Table 20: Landlessness in Bihar MCDs (%) District Hindu Muslim SC & ST OBC GC* Total OBC GC* Total Araria 78.79 52.33 28.57 62.26 61.54 72.12 63.10 Bettiah 82.70 59.68 35.42 67.66 70.75 48.45 65.08 Darbhanga 84.42 60.18 23.81 67.24 85.54 54.11 67.25 Katihar 74.11 59.75 42.86 63.94 61.84 60.47 60.90 Kishanganj 71.91 49.57 75.00 59.62 55.86 48.55 52.86 Purniya 72.03 56.98 80.77 64.56 67.18 57.26 65.52 Sitamari 85.91 49.82 36.71 58.48 77.06 65.45 72.09 Average 79.92 55.91 39.55 63.78 65.94 57.16 62.72

Table 21: Employment in Agriculture & Allied Activities in Bihar MCDs District Hindu Muslim SC & ST OBC GC* Total OBC GC* Total Araria 80.71 64.56 45.00 71.54 59.46 57.08 59.64 Bettiah 77.44 66.37 59.70 70.65 65.22 60.68 64.19 Darbhanga 47.59 49.02 45.78 48.09 33.95 34.27 34.14 Katihar 75.88 68.04 73.33 70.57 63.01 50.00 55.70 Kishanganj 74.01 64.16 44.44 68.16 56.37 59.49 57.59 Purniya 86.15 76.00 73.85 79.76 63.13 68.44 64.20 Sitamari 68.82 57.59 35.48 58.04 21.27 30.60 25.86 Average 71.30 63.48 50.65 65.72 56.05 50.47 54.09 *GC: General category

The proportion of Muslim workforce in secondary sector activities like petty production and construction is higher with 32.01%, while only 19.98% of working Hindus are in this sector

(Annexure 20). In Sitamari (58.32%) and Darbhanga (44.16%), the share of secondary sector occupation for Muslim is high. Table 23 shows that there are districts like Kishanganj, Sitamari and Darbhanga where one-third of the Hindu workforce is working in the secondary sector. In

Sitamari, a very high proportion of Muslim-General (54.09%) and Muslim-OBC (61.90%) workers are engaged in the secondary sector. In contrast, Purniya offers a relatively very low level of secondary sector employment, especially to the Hindu community.

In the case of employment in services, the Hindu workforce has a marginally higher share (14.30%) compared to the Muslim community (13.90%) (Annexure 21). For Hindus-

32

General, service is the second most important source of employment (28.20%) after agriculture.

It is almost double that of any other community (Table 24). In Sitamari 39.52% of Hindu-

General workers are in services, and Darbhanga is another district that provides a relatively higher share of employment in services. Katihar, Kishanganj and Purniya are lowest in service sector employment. This may be so in Purniya because of overall backwardness or because occupationally Purniya stands out as the most agriculturally dominated district, with 79.76% of

Hindu and 64.20% Muslim workforce engaged in agriculture. Darbhanga, in contrast is a district where non-agricultural occupations account for the majority of the workforce, not only for

Muslims but also for the Hindus. But in the case of Muslims, non-agricultural activities account for almost two-thirds of the workforce, while for Hindus it is a little over 50%. Incidentally, the incidence of migration is also higher in Darbhanga, and it is more or less the same for both the communities at about 16% (Annexure 22). Overall, in Bihar MCDs, migration among Muslims is higher (14.25%) compared to 11.78% for the Hindus. Katihar shows the lowest level of migration for Hindus as well as Muslims. What is striking is the very high rate of migration

(24.02%) among Hindus-General in Darbhanga. Table 25 holds yet another dimension of the

‘Bihar Paradox’ - i.e. the higher the place in the caste-hierarchy, the higher appears to be the tendency to migrate - among both Hindu and Muslim communities. However, this could be in search of greener pastures for the upper echelons and a search for subsistence for the lower ones!

Table 22: Caste/ Community-wise Land* Ownership and Occupation in Bihar MCDs (%) Caste / Community Landlessness) Employment in Agriculture Employment in Non- & Allied Activities Agricultural Activities Hindu – General 39.55 50.65 49.35 Hindu – OBC 55.95 63.48 36.52 Hindu – SC/ST 79.92 71.30 28.70 Muslim – General 57.16 50.47 49.53 Muslim – OBC 65.94 56.05 43.95 *To be technically correct it could be called “Landlessness”

Table 23: Caste/ Community-wise Secondary Sector Employment in Bihar MCDs Caste / Community % Share in Secondary Sector Employment Average for MCDs Lowest / District Highest / District Hindu – General 21.15 13.85 33.33 (Purniya) (Kishanganj)

33

Hindu – OBC 20.98 12.50 30.7 (Purniya) (Sitamari) Hindu – SC/ST 18.46 7.09 33.99 (Purniya) (Darbhanga) Muslim – General 34.63 21.31 54.09 (Purniya) (Sitamari) Muslim – OBC 30.62 25.97 61.90 (Purniya) (Sitamari)

Indebtedness and Sources of Credit

The incidence of indebtedness in Bihar MCDs is higher than in Uttar Pradesh, but the situation of the share of formal institutional sources is much worse in Bihar than even the poor situation in U.P. Across the MCDs in Bihar, the incidence of indebtedness does not show much variation across castes and communities. Among the Hindu community, it is marginally higher at

47.21% compared to 45.05% for Muslims (Annexure 23). Table 26 shows that the share of institutional sources in the credit provided is abysmally low for both the communities – Hindus

11.46% and Muslims 10.32%. The highest level is in Kishanganj where it is 33.33% for Hindus and 20.45% for Muslims; and the most dismal case is Bettiah where it is just 5% for both the communities. Though there are marginal caste / community differences, there does not seem to be any pattern, except that the overall institutional sources are dismally low.

Table 24: Caste/ Community-wise Tertiary Sector Employment in Bihar MCDs

Caste / Community % of Employment in Tertiary Activities Average for MCDs Lowest / District Highest / District Hindu – General 28.20 6.67 39.52 (Katihar) (Sitamari) Hindu – OBC 15.55 11.50 24.95 (Purniya) (Darbhanga) Hindu – SC/ST 10.24 5.73 18.42 (Kishanganj) (Darbhanga) Muslim – General 14.91 10.25 20.91 (Purniya) (Darbhanga) Muslim – OBC 13.34 8.45 22.84 (Bettiah) (Darbhanga)

Table 25: Caste/ Community-wise Migration in Bihar MCDs

Caste / Community Rate of Migration (%) from MCDs Average for MCDs Lowest / District Highest / District Hindu – General 16.57 5.56 24.02 (Katihar) (Darbhanga) Hindu – OBC 11.67 9.02 15.16 (Katihar) (Darbhanga) Hindu – SC/ST 10.90 7.36 14.59 (Katihar) (Purniya) Muslim – General 15.46 10.10 18.14

34

(Araria) (Sitamari / Darbhanga) Muslim – OBC 13.49 9.40 17.60 (Katihar) (Sitamari)

35

Table26: Institutional Sources (%) - Bihar Hindu Muslim SC & ST OBC GC* Total OBC GC* Total Araria 13.04 24.47 33.33 21.23 16.26 11.84 15.14 Bettiah 3.42 6.10 10.34 5.31 2.86 12.50 5.21 Darbhanga 3.65 9.68 8.33 7.01 1.94 2.50 2.24 Katihar 20.00 17.70 25.00 18.47 15.00 8.59 11.65 Kishanganj 31.58 34.21 33.33 23.91 16.67 20.45 Purniya 6.12 11.46 7.14 9.43 5.28 16.67 7.31 Sitamari 7.59 10.32 27.03 11.81 5.88 8.75 7.74 Average 7.56 13.25 15.87 11.46 10.16 10.62 10.32 *GC: General category

Access to Amenities

It is very difficult to imagine that there could be such a large number of districts in any one state as in Bihar MCDs, with a blanket dismal situation prevailing with respect to almost all the amenities identified as basic to a decent living. There is much propaganda about better performance of Indira Awas Yojana (IAY) in Bihar, but the reality appears to be quite the contrary. The share of houses with pucca walls is as low as 12.63% for Hindus and 6.48% for

Muslims (Table 27). Both are very low but the Muslim situation seems to be such that it could not be any worse. The ‘best’ performing district, Bettiah, shows figures of 18% for Hindus and

13% for Muslims. The condition in Purniya is also dismal, with 9% for Hindus and 3% for

Muslims. The relatively better housing of SCs/STs co mpared to the Muslim community may be because of the former’s better reach to IAY. The figures for electricity connections to houses show that these districts are at least a century behind some of the states in India (Table 28). The figures for electrification among Bihar MCDs range from 8% in Kishanganj to 14% in Purniya for Hindus, and from 2.63% in Katihar to 14% in Bettiah for Muslims. In this situation, one can imagine what would be the state in terms of W.C toilets: Only about 7% of Hindu households and 8% Muslim households have these facilities! (Table 29). Potable drinking water access, though much lower than the national level, is not so distressing at 53% for Hindus and 66% for

Muslims (Annexure 28). With regard to amenities, both the communities are sailing in the same abysmal boat, which is substantially due to the absence of administrative and political

36 commitment. Though the Hindu-General category shows a relatively high level, it too is nowhere near what may be called a decent level of coverage under basic amenities (Figure 8).

Figure 8: Basic Amenities of Pucca House, Electricity and W.C. Toilet Facility in Bihar MCDs (% of Households) 22.62 22.17

25 21.27

20 12.26 11.59 12.07 15 7.79 12.24 6.85 10.16 8.24 7.79 5.36 10 5.5 1.83 5 % of Households

0 Hindu-General Hindu-OBC Hindu-SC/ST Muslim-General Muslim-OBC Pucca House Electricity W.C. Toilet

Table 27: District-wise Access to Pucca House in Bihar MCDs % District Hindu Muslim SC & ST OBC GC* Total OBC GC* Total Araria 3.79 11.63 7.14 8.18 4.52 7.69 5.17 Bettiah 20.68 12.65 33.33 18.03 10.67 20.62 13.13 Darbhanga 8.54 11.06 23.81 11.13 5.42 11.26 8.82 Katihar 17.86 13.14 25.00 14.89 3.51 3.65 3.57 Kishanganj 8.99 18.64 0.00 14.22 7.00 5.42 6.30 Purniya 11.02 7.56 11.54 9.18 1.55 8.06 2.92 Sitamari 10.07 9.16 18.99 10.98 10.00 10.30 9.88 Average 12.26 11.59 21.27 12.63 5.50 8.24 6.48

Table 28: District-wise Electrification in Houses in Bihar MCDs (%) District Hindu Muslim SC & ST OBC GC* Total OBC GC* Total Araria 1.52 15.12 14.29 9.43 5.20 12.50 6.77 Bettiah 9.70 14.23 16.67 12.45 8.70 27.84 13.97 Darbhanga 9.55 10.18 21.43 10.92 10.24 13.42 12.09 Katihar 5.36 11.86 12.50 9.83 2.63 2.66 2.63 Kishanganj 8.99 6.78 25.00 8.06 7.00 5.42 6.30 Purniya 4.24 16.86 38.46 13.92 9.31 21.77 11.84 Sitamari 5.37 9.16 22.78 10.18 17.06 6.67 11.63 Average 6.85 12.07 22.17 10.90 7.91 10.16 8.73

Table 29: District-wise In-house Toilet Facility in Bihar MCDs (%) District Hindu Muslim SC & ST OBC GC* Total OBC GC* Total Araria 3.03 6.98 7.14 5.35 3.62 1.92 3.21 Bettiah 0.84 3.16 18.75 3.53 7.11 22.68 11.17 Darbhanga 0.50 5.31 14.29 4.07 4.22 14.72 10.33 Katihar 7.14 15.25 12.50 12.64 10.96 12.96 12.03 Kishanganj 3.37 6.78 0.00 5.21 6.25 10.47 7.91 Purniya 0.00 6.40 11.54 4.43 1.33 4.03 1.89 Sitamari 0.67 9.52 37.97 11.38 9.41 16.97 12.79 Average 1.83 7.79 22.62 6.72 5.36 12.24 7.87 *GC: General category The PDS performance too is far below par but it does work, with 25% of Hindu and 27% of Muslim households accessing it (Table 30). The functioning varies from only 5% to 6% of the households of both communities accessing it in Sitamar,i to about 50% of the households in Kishanganj. Kishanganj is a district where Muslims constitute 67.6% of the total population.

37

One silver lining is that in accessing the PDS, SC/ST households do much better than all other categories. Table 30: Access to PDS (%) in Bihar MCDs Hindu Muslim SC & ST OBC GC* Total OBC GC* Total Araria 31.78 26.67 0.00 27.78 19.91 29.70 21.53 Bettiah 32.07 25.69 16.67 27.70 19.37 19.59 19.83 Darbhanga 26.67 13.36 7.89 18.67 11.04 7.56 9.02 Katihar 48.21 37.71 NA 40.17 46.05 44.19 44.92 Kishanganj 58.43 42.37 25.00 48.82 52.14 51.62 51.91 Purniya 25.86 18.60 26.92 21.97 14.96 9.76 13.64 Sitamari 9.40 5.13 1.27 5.79 5.88 3.03 4.65 Average 31.06 22.52 9.30 24.74 25.92 27.85 26.57 *GC: General category

4.3 Jharkhand

The records of MCDs in the country show only four districts of Jharkhand, but five districts were actually surveyed in Jharkhand by including Sinmdega district, which does not figure in the original list. The social fabric of Jharkhand presents a more complex overlay of religion over tribe. Table 31 shows the religious composition of population in the five MCDs.

The religious category ‘others’ listed here does not figure in the minority religions of India recognized under the Minorities Act. Further, except the Muslim community, the other religions in Jharkhand include a substantial proportion of ST population. The results of the survey reports may not give a completely satisfactory representative picture because of a very thin sample, or under-representation of certain communities in the sample.

Table 31: Religious Composition of Population in MCDs in Jharkhand (%) District Hindu Muslim Christian Others* ST** 1. Gulma 24 8 29 39 72 2. Pakur 46 32 - 22 45 3. Ranchi 42 10 43 5 53 4. Sahibganj 60 32 7 1 29 5. Semdega 32 3 50 15 79

*These are tribal groups which claim separate religious identity like ‘Sarana’ in Gulma or ‘Sanatan’ or ‘Adi Dharma’ in Pakur. **STs cut across all religions except Muslims. Co nsiderable proportion of Hindus is tribal. Almost the entire population of Christians is converted from STs and ‘others’ again belong to different Schedule Tribes.

There are problems in comparing the data available on different indicators across the districts and religious groups. In terms of socio-economic indicators like literacy and school

38

enrolments, Christians fare much better, except in Sahibganj. In literacy, Muslims do much

better than Hindus and ‘Others’ in all the five districts (Table 32).

Table 32: Literacy and School Enrolment (6-16 years) in MCDs in Jharkhand (%) District Hindu Muslim Christian ‘Others’ Literacy Never Literacy Never Literacy Never Literacy Never Enrolled Enrolled Enrolled Enrolled 1. Gulma 60 1 64 3 84 0 63 3 2. Pakur 57 5 68 4 60 1 58 3 3. Ranchi 67 5 79 4 75 3 61 5 4. Sahibganj 63 4 69 7 57 16 43 41 5. Semdega 59 3 72 - 80 2 42 0

In terms of amenities like pucca housing and in-house drinking water facilities the overall

situation in all the districts is very poor, but the condition of Christians and ‘Others’ is much

worse than others across the districts (Table 33).

Table 33: Housing and Drinking Water Facility in MCDs in Jharkhand (%) District Hindu Muslim Christian ‘Others’ Pucca Inhouse Pucca Inhouse Pucca Inhouse Pucca Inhouse House Drinking House Drinking House Drinking House Drinking Water Water Water Water 1. Gulma 23 8 8 1 2 11 1 7 2. Pakur 19 12 29 20 6 8 3 2 3. Ranchi 25 27 23 21 9 ? 3 ? 4. Sahibganj 19 52 39 58 8 7 0 11 5. Semdega 14 1 2 0 2 12 0 20

4.4 Uttarakhand

Hardwar and Udham Singh Nagar are the two MCDs in Uttarakhand and both are

identified in the B1 category, meaning that these two districts lag in literacy and work

participation criteria but not in basic amenities. In Hardwar, the minority communityconstitutes

35%, most of them Muslims. In Udham Singh Nagar, the minority communities constitute 32%,

with half of them being Muslim and the other half Sikh.* In spite of certain skewed sampling

design, the results do represent certain interesting pattern.

The demographic features of the two districts show (Table 34) that the Muslim

households are on an average larger and their dependency ratios are higher compared to the

other two communities. But sex-ratio of Muslim community is higher compared to the other

* The sample design of Udham Singh Nagar is highly skewed, with 16% of Muslim population constituting 44% of the sample households and with 1578% (Pls check this. What is the correct figure?) of Sikh population ending with an under-representation constituting only 8% of the sample. 39 two communities in the two districts. Literacy, school enrolments and dropout rates show that

Muslims lag behind the Hindu community in Hardwar (Table 35) and possibly in Udham Singh

Nagar.

Table 34: Demographic Characteristics of MCDs in Uttarakhand District / Community Average Size of Household Sex-Ratio Dependency Ratio 1. Hardwar a. Hindu 5.7 789 0.68 b. Muslim 6.1 830 0.87 2. Udham Singh Nagar a. Hindu 4.6 876 0.68 b. Sikh 4.7 757 0.44 c. Muslim 5.6 915 0.85

Table 35: Literacy and Education (6-16 years) in Uttarakhand MCDs (%) District / Community Literacy Never Enrolled Dropouts Male Female All Male Female All Male Female All 1. Hardwar a. Hindu 86 82 84 12 16 14 1.8 1.9 1.9 b. Muslim 70 65 68 25 29 27 4.6 5.2 4.9 2. Udham Singh Nagar a. Hindu 70 66 68 - - 0 - - - b. Sikh 83 76 80 - - 0 - - - c. Muslim 67 62 65 - - 0 - - -

Occupationally, all the three communities in Hardwar and Udham Singh Nagar are mainly dependent on agriculture (Table 36) but the proportion of cultivators among Muslim community is much less than that among Hindus and Sikhs. The proportion of Muslim workers in the non-agricultural sector is more than the other two communities, especially in Udham

Singh Nagar.

Table 36: Broad Categories of Employment in Uttarakhand MCDs (%) District / Community Cultivator Agricultural Non-Agricultural Other Regular Labour Labour Employment 1. Hardwar a. Hindu 27 49 18 6 b. Muslim 19 55 22 3 2. Udham Singh Nagar a. Hindu 21 67 8 4 b. Sikh 23 68 3 5 c. Muslim 9 72 14 5

In terms of basic amenities like housing, electricity, and drinking water access, the

Muslim community is on par with the Hindus in Hardwar but far behind both Hindus and Sikhs in Udham Singh Nagar (Table 37). But in the case of in-house toilet facilities, they are much better off than both Hindus and Sikhs. Except this factor of in-house toilets, the Sikh community enjoys much higher levels of attainment in amenities.

Table 37: Access to Basic Amenities in Uttarakhand MCDs (%)

40

District / Community Semi Pucca / Pucca Tapin House Domestic Electricity In-House Toilet House 1. Hardwar a. Hindu 86 4 53 35 b. Muslim 84 2 53 52 2. Udham Singh Nagar a. Hindu 78 76 77 45 b. Sikh 97 83 99 56 c. Muslim 67 72 69 87

In accessing institutional child deliveries, Hindus and Muslims lag far behind[M5], and in

case of immunization at least in polio drops, all communities appear to be doing better[M6]. But

provision of health facilities through governm ent dispensaries seems to be in a pathetic state in

Hardwar. In the case of indebtedness among the Muslim community, the incidence is higher

(41%) in Hardwar compared to Udham Singh Nagar (29%), but the institutional access to credit

is lower (19%) in Hardwar than in the latter (60%). Hindus of Hardwar have higher incidence of

indebtedness (49%) than those of Udham Singh Nagar (14%). The Sikh community shows

lower incidence of indebtedness (14%) as well as lower institutional sources of credit (24%).

Ta ble 38: Health Related Indicators in MCDs of Uttarakhand (%) District / Community Institutional Immunization Government Deliveries (Polio) Hospital Access 1. Hardwar a. Hindu 22 98 4 b. Muslim 16 99 6 2. Udham Singh Nagar a. Hindu 6 90 - b. Sikh 50 85 - c. Muslim 14 80 -

Table 39: Access to Institutional Credit and PDS in Uttarakhand MCDs (%) District / Community Incidence of Indebtedness Share of Formal Sources Access to PDS by BPL Households 1. Hardwar a. Hindu 49 35 65 b. Muslim 41 19 60 2. Udham Singh Nagar a. Hindu 14 35 - b. Sikh 14 24 - c. Muslim 29 60 -

41

4.5 Haryana

Two MCDs, Sirsa and Mewat (), are identified as B1 category districts, which

means they face deficits in literacy and work participation and not in amenities. It is also strange

that districts not far from the national capital region have deficiencies in socio -economic

indicators, whereas remote Nicobar or Leh have a better standing on these counts.

Mewat district was formed as the 20th district of Haryana in 2005 by carving out four

Tehsils from Gurgaon and one from . This bifurcation left Gurgaon with only 10% of

minority population while in the newly formed Mewat, minorities, mostly Muslims, constituted

71%.Hence the choice for the MCD survey was Mewat rather than Gurgaon. Mewat is also

predominantly rural with 93% of the population living in rural areas. The other MCD from

Haryana is Sirsa with 74% rural population. The religious composition of Sirsa shows 68%

Hindu, 31% Sikh and the remaining (0.6%) constitute Muslims and Christians. Scheduled Castes

account for a very high proportion of 27% in the total population, and 44% of Hindus and 36%

of Sikhs are SCs. Table 40 shows that the main minority community in Mewat is Muslim, and in

Sirsa it is Sikh. The sample size of other minorities in these respective MCDs is negligible and

hence is not included in the analysis.

Table 40: Religious and Social Composition Sample Households of MCDs in Haryana (%) MCD Hindu Muslim Sikh Others 1. Mewat* 16 83 Nil Negligible 2. Sirsa* 56 1 40 2 *Does not add up to 100 because of rounding.

Table 41 shows that within a relatively small state of Haryana, there are variations in the

demographic features not only between communities but also within the communities. The

Hindu community in Mewat shows larger family size but lower dependency ratio, lower sex-ratio

and higher literacy compared to Sirsa. The Muslim community in Mewat has higher family size

but much lower dependency ratio, higher sex-ratio but lower literacy compared to Hindus. In

Sirsa, the Sikh community shows same size of household, lower dependency ratio but lower sex-

ratio and higher literacy compared to Hindus.

42

Table 41: Certain Demographic Features of MCDs in Haryana MCD/ Average Size Dependency Sex Ratio Literacy (%) Community of Hh. Ratio Male Female Persons 1. Mewat a. Hindu 5.57 0.40 819 72 43 59 b. Muslim 6.81 0.31 843 68 33 52 2. Sirsa a. Hindu 5.0 0.71 869 68 50 60 b. Sikh 5.0 0.66 829 69 55 63

Inter-District and Intra-District Differences

Inter-district differences are far more striking than inter-community differences. The

overall conditions in Sirsa are distinctly better than in Mewat. The overall condition of the

Muslim community in Mewat is worse than the Hindu community. This comes as a surprise

because the Muslims of Mewat are known to be of Meo -origin, they have a self -image of being

former ruling Rajputs and are known to be landed people with agriculture as major occupation

(Saberwal, 2010). The overall condition of the Sikh community in Sirsa is much better than that

of the Hindus in Sirsa. The Hindu community in Mewat is far behind its counterpart in Sirsa.

For instance, ‘institutional deliveries’ are 12% for Hindu households and 7% for Muslims in

Mewat, while they are 28% for Hindus and 41% for Sikhs in Sirsa. Similarly, immunization of

children (at least against polio) is 65% and 66% for Hindu and Muslim households respectively,

in Mewat, whereas it is as high as 97% and 99% for Hindu and Sikh households in Sirsa.

A striking feature is the higher landlessness among Hindu households in Mewat (72%) as

well as Sirsa (71%), whereas it is much lower for Muslim households (44%) in Mewat and Sikhs

(48%) in Sirsa. Work participation as well as occupational distribution too reveals substantial

inter-district variation. Table 42 shows work participation rates (WPR) are lower in Mewat

compared to Sirsa. The overall female WPRs are lower, and these are much lower in Mewat, and

WPRs are higher for Hindu males as well as females compared to Muslim counterparts. The

male WPRs for Hindu and Sikh communities in Mewat are reported at unusually high levels of

85% and 83% - which has raised some doubts about the method of calculation used. Another

unusual feature is the occupational distribution in Mewat, where the primary occupation for

Hindu households is in secondary sector (53%) and for Muslim households it is agriculture

43

(48%). In Sirsa, for both communities agriculture is the main occupation, and it is higher for

Sikh households (71%) than the Hindu (63%).

Table 42: Work Participation Rate and Occupational Distribution in MCDs of Haryana (%) MCD/Community Work Participation Rate Employment Male Female Persons Agriculture Secondary Services & Allied Sector 1. Mewat a. Hindu 53 10 34 26 53 21 b. Muslim 48 8 28 48 32 20 2. Sirsa a. Hindu 85* 30 59 63 27 10 b. Sikh 83* 28 56 71 22 7 * These figures do raise questions on the method of calculation.

In access to basic amenities too Sirsa is far ahead of Mewat in terms of all indicators.

Table 43 shows that though Mewat is far behind Sirsa in access to amenities, the inter- community differences are far lower with Hindu, households having an edge over the minority, except in the case of in-house toilets. In Sirsa, Hindu households have much better access to amenities compared to their counterparts in Mewat, but much less than the Sikh community in

Sirsa. This calls for attention to differentiation of approach to MCDs within a state.

Table 43: Access to Basic Household Amenities in MCDs of Haryana (%) MCD/Community Semi Pucca / Pucca Electricity In-House Taps In-House Toilets House 1. Mewat a. Hindu 76 59 20 12 b. Muslim 77 55 17 14 2. Sirsa a. Hindu 83 74 62 73 b. Sikh 92 84 68 84

4.6 Jammu and Kashmir

Leh (Ladakh) is the only MCD from Jammu and Kashmir. It is under the category of B2 which indicates that the deficits are in the amenities rather than socio-economic indicators.

Buddhists who constitute 77.3% of the population of Leh are the largest religious group, followed by Muslims with 13.78% and Hindus with 8.16%. But as a social group, Scheduled

Tribes constitute 82% of the population, and Buddhists are essentially comprised of different

STs. The domina nt composition of STs is also reflected in the constitution of the Leh Hill

Development Council under the Ladakh Autonomous Hill Development Council Act 1995, which provides for decentralized democratic system.

44

In spite of its remoteness, Leh has much better educational achievement than J & K as a whole. The literacy rate of Leh is 65% compared to 50% of J&K; and almost all villages in Leh have a primary school, whereas only 88% of J&K villages have primary schools. There is hardly any difference between the Buddhist and Muslim households for most of the indicators except for sex-ratio which is higher for Buddhists (1012) compared to 972 for Muslims. Literacy is high at 79% for Muslims and 74% for Buddhists. Landlessness is very low at 7 to 8% for both the communities. Work participation rates for both male and female Muslims and Buddhists is high, in the range of 56% to 60%. The main source of employment for both Muslims and Buddhists is salaried employment (50%), mostly in government service. Agriculture provides a low share of about 12% of total employment. Except for Muslim women, the majority of whom are engaged in own farming, agriculture is an insignificant source of employment.

There is almost zero indebtedness among both the ethnic groups. About 12% of

Buddhist and 3% of Muslim households report migration and most of the migration is for a long -term. There is a high level (more than 95%) of school enrolment among both groups, but

78% of Muslims and 63% of Buddhists have schools located at a distance of more than 4 kms.

Health facilities are a cause for concern in the case of both the religious groups. Dependence solely on government hospitals is reported by only 25% of households, and the majority of them depend on both private and public facilities. Given the remoteness, such a situation may result in lack of health security for those who cannot afford private health care. However, the silver lining is that almost all children are at least partly immunized by government provision, and institutional child deliveries range from 82% for Muslims to 86% for Buddhists, and all these institutions are government hospitals. However, low access to ICDS ranging from 20% for

Buddhists to 26% for Muslims, reflects poor performance.

The overall amenities situation too compares much better than other MCDs. All Muslim households and 86% of Buddhist households have electricity. All Buddhist households have in- house toilet facilities while 97% of Muslims have similar facilities. Muslims have better access

45

(67%) to publicly provided drinking water facilities while only 44% of Buddhists have such access. Access to PDS is also low, especially for the Muslim community (21%). Access to higher education for children and better employment facilities are the aspirations of both

Buddhists and Muslims.

4.7 Delhi-National Capital Region

The North-East district of the Delhi National Capital region is another exception to the rule of MCDs being essentially rural, as it is predominantly urban (92%). The sampling , analysis and presentation of the results of the North-East MCD are presented in terms of the following three locational categories:

Category I: Localities with minority population between 0 to 25% Category II: Localities with minority population between 26 to 75% Category III: Localities with minority population between >75%

Table 44 provides information on some key indicators across the categories. The indicators on education like children attending English medium schools or private schools and the limited information on employment suggest that Category I localities are much better in economic status. But in the case of amenities, except for drinking water, there is no such difference, for instance in domestic connection of electricity and in-house toilet facilities, in which Category II & III locations with higher concentration of minority population fare better.

Table 44: Locational Differences in Terms of Socio-economic and Amenities Indicators* - North-East District of Delhi (%) Indicator Cate gory I Category II Category III 1. Literacy Male 78 78 72 Female 70 70 63 Persons 75 74 67 2. English Medium 34 17 21 3. School Type a. Govt. School + Aided 65 73 86 b. Private 30 22 10 c. Madrassa 0 4 4 4. Work Status* a. Professional / Technical work 15 10 7 b. Service Workers Rented / Temporary 22 15 11 5. Drinking Water Tap Water 67 53 33 6. Electricity connection 94 94 94 7.In-House Toilet 85 95 95 *There is no clear information provided on employment and housing.

46

V

Easte rn Region

The Eastern Region accounts for the second largest number of MCDs (25). Three states viz. West Bengal (12), Assam (13), and Orissa (1) are included in this region.

5.1 West Bengal

West Bengal with about 15% of the country’s total Muslim population has the second largest concentration of the community. As pointed out earlier, 97.6% of Muslims are classified as Muslim -General and only 2.4% constitute Muslim-OBCs. For this reason, the entire analysis here is confined to Muslims-General. Of the 90 MCDs, as many as 12 are in West Bengal.

Similarly, Hindu-OBCs constitute only 8.4% of the Hindu population, while Hindus-General account for almost 50% percent, and another 42% are SCs/STs in West Bengal. Compared to national literacy rate of 67.30% (2005), literacy rates in West Bengal MCDs are lower except for

Hindus-General, who is only marginally higher at 70.6% (Annexure 25). But literacy rate of

Muslims-General is only 53.4%, way below others (Table 45). The inter-district variations are also wide. In the case of those with ‘Matric and higher’ levels of education, the Hindu-Muslim differences vary widely, with 20% for the Hindu community to only 11.4% for the Muslim community. In cutting-edge education levels, the Muslim community is at a disadvantage and the gap in ‘Matric and above’ levels is substantially higher than in other states. Figure 9 shows the steep communal incline, with Muslims-General ending up below the level of SCs/STs. In the relatively better performing district like Haora ‘matric and above’ represent 27.44% in the case of

Hindus, and only 10.56% for Muslims; and the lowest level for Hindus is 7.87% in Birbhun and

3.39% for Muslims in Dakshin Dinajpur.

47

Table 45: Literacy Rates (6 years & above) in West Bengal MCDs Caste / Community Percentage of Literates in the age group of 5 and above Average for MCDs Lowest / District Highest / District Hindu-General 70.6 43.8 92.6 (Malda) (Haora) Hindu-OBC 62.5 36.4 92.1 (Haora) (Birbhum) Hindu-SC/ST 65.0 35.0 91.8 (Malda) (Haora) Muslim -General 53.4 49.8 95.9 (Nadia) (Haora)

Figure 9: Proportion of Adult Population with 'Matric and Above' in West Bengal MCDs

30 27.6 25 25.1 20 15 Series1 12.7 10 11 5 0 % with 'Matric and Above' Hindu- Hindu-OBC Hindu-SC/ST Muslim- General General

Basic Amenities

Compared to the national level, the pucca housing situation for both Hindus and Muslims

in West Bengal leaves much to be desired. However, compared to the other states with high

concentration of MCDs like U.P., Bihar and Assam, the situation in MCDs in the state is not as

dismal. The proportion of households among the Hindu community with pucca housing is higher

with a range of 40% to 55%, whereas it is much lower for the Muslim community, with 20% to

40%. Murshidabad and Maldah reflect very poor housing for over 80% of Muslim households.

There is no escaping caste-community hierarchy in access to pucca houses even in West Bengal.

Pucca housing is available only for 7% of SCs/STs, it si more than double that for Hindu-OBCs

(15.9%) and more than three times for Hindus-General. Muslims-General are only marginally

above SCs/STs (Table 46).

48

Table 46: Caste/Community-wise Pucca Housing in West Bengal MCDs Caste / Community Percentage of Households with Pucca Houses Average for MCDs Lowest / District Highest / District Hindu-General 26.3 3.7 39.3 (Dakshin Dinajpur) (Haora) Hindu-OBC 15.9 5.0 27.6 (Dakshin Dinajpur) (North 24 paraganas) Hindu-SC/ST 7.0 1.0 22.7 (Coochbehar) (Haora) Muslim-General 9.9 1.3 19.0 (Coochbehar) (Murshidabad)

What is perplexing is the neglect of electrification of houses in West Bengal. Except Haora, in the remaining 11 MCD districts, more than 66% of Muslim households do not have electricity (Annexure 28). The condition of Hindu households is even worse. Except Haora and Nadia, in the remaining 10 MCDs more than 80% of Hindu households do not have electricity. Table 47 shows that caste-community hierarchy is reflected in household access to electricity. Hindus-General are at the top (59.7%), SCs/STs at the bottom (25.7%) and Muslims-General marginally above SCs/STs. And Coochbehar with low electricity connectivity for households is a lot like Purniya of Bihar. Unlike U.P. and Bihar where access to potable drinking water is much better than the national level, the situation in Bengal is worse. For the Hindu community as a whole, it is 43.1% and for Muslims it is only 37.6%,on par with SCs/STs. But in Dakshin Dinajpur, it is worse for both communities, with hardly 10% of the households having access to potable water inside the house (Annexure 29). The W-C toilet facilities are better than in U.P. and Bihar, but there are substantial caste-community as well as regional differences (Table 48). The proportion of Hindu-General households with W.C. toilet facilities is almost double (64.6%) that of the Muslim-General (33.5%) level, which is marginally less than that of SCs/STs (34.5%). Regionally, North-24 Paraganas and Nadia are much better, while Uttar-Dinajpur and Malda are at the bottom. While Haora stands in a relatively better position for both the communities, Nadira has better toilet facilities for the Muslim community. The poorest in the scale is Mursheedabad where the facility is hardly for 10% of the households of either of the communities.

49

Table 47: Caste/ Community-wise Electricity in West Bengal MCDs Caste / Community Percentage of Households with Electricity Average for MCDs Lowest / District Highest / District Hindu-General 59.7 25.2 87.1 (Coochbehar) (Haora) Hindu-OBC 45.4 11.1 65.6 (Coochbehar) (Murshidabad) Hindu-SC/ST 25.7 10.8 72.2 (Coochbehar) (Haora) Muslim-General 30.3 6.3 65.9 (Coochbehar) (Haora)

Table 48: Caste/ Community-wise W.C. Toilet Facilities in West Bengal MCDs Caste / Community Percentage of Households with W.C. Toilet Facility Average for MCDs Lowest / District Highest / District Hindu-General 64.6 29.9 86.6 (Birbhum) (North-24 paraganas) Hindu-OBC 51.0 18.2 89.2 (Uttar-Dinajpur) (Nadia) Hindu-SC/ST 34.5 6.3 77.4 (Malda) (North-24 paraganas) Muslim-General 33.5 7.2 79.4 (Uttar-Dinajpur) (North-24 paraganas)

(Because of serious data problems we are not able to present detailed Tables on different dimensions for West Bengal)

5.2 Assam

Assam with about 7% of the total Muslim population has the fifth largest concentration of the community in the country. Muslims account for about 30% of the state’s population. Of the 13 MCDs in the state, 12 are Muslim MCDs. The remaining one is the North Cachar Hills district, and is a Christian MCD, outperforming the others in all socio -economic indicators. Its inclusion is based on amenity deficits and in any case, this paper confines itself to the Muslim

MCDs.

Like West Bengal, Muslims in Assam are also classified predominantly as general (97%).

It is worth noting that in Assam, among Muslims, no one was reported as belonging to SCs, and

OBC presence among the community is confined to only three districts, viz., Darrang,

Hailakandi and Cachar. Thus, most of the Muslims in Assam are reported as belonging to the

‘general’ category of Asrafs. Because of the thin sample of Muslim-OBC, the present analysis is confined to Muslims-General in Assam.

The spread of the Muslim population in Assam is rather wide, especially near the border with Bangladesh. Compared to Bihar and Uttar Pradesh, the average size of the family in Assam 50 is smaller for both the Hindu and Muslim communities. However, as in the other cases, in

Assam too the household size of Muslims is larger (5.69) than the Hindus (5.06). What is interesting is that with a couple of exceptions, there is a more or less even spread of the size of families across the districts for both the communities (Annexure 31). Assam has a better sex ratio compared to many other states. Unlike U.P. and Bihar, the range of variation in sex-ratio across the districts is much smaller for both the communities (Figure 10). The same holds for intra-community variation among Hindus. The Assam MCDs show that the difference in sex ratio between Hindus and Muslims is marginal, and in contrast to the other states discussed above, the Hindu sex-ratio is marginally better than the Muslim one (Annexure 32), but the story repeats itself when it comes to the dependency ratio (Figure 11). Among the Muslims, the dependency ratio is much higher (87%) compared to the Hindus (55%), but compared to the

Muslim community in Bihar or UP, it much less (Annexure 33).

Figure 10: Range of Sex-Ratio Across Religious Communities in Assam MCDs Gopalpara 1200 972 998 1000 814 Darrang 800 912 938 600 Hailakandi 810 400 Sex-Ratio 200 0 Lowest Average Highest All Hindu Muslim-General

Figure 11: 'Dependency Ratio'* Among Hindu and Muslim Communities in Assam MCDs

120 Nagaon, 97 100 87 80 Dhubri, 73 Cachar, 67 60 55 40 N.C.Hills, 26 20 0 Lowest Average Highest All Hindu Muslim-General *Percentage of Non-earning Members to Earning Members

Literacy and Educational Levels

Literacy and education in Assam MCDs stands on a better footing – much higher than the national level and more equal across communities than in the other states. The Hindu community has a marginal edge compared to the Muslims in literacy and ‘never enrolled’.

Literacy levels among the Hindus are higher (80.4%) than the Muslims (71.8%) in the MCDs as a whole and also in all the districts except Cachar (Table 49). Figure 12 brings out the difference

51 in literacy among the two communities. A similar picture emerges regarding the status of those

‘never enrolled’ being 2.6% for Hindus and 3.9% for Muslims. Though the difference is little and low, there are locations of high disparity. For instance, the high level of ‘never enrolled’

11.4% for Hindus and 18.4% for Muslims in Kokrajhar could be a cause for concern (Annexure

34). In contrast, Marigaon shows almost hundred percent enrolment rate, especially for the

Muslim community. In terms of school education, the Muslim community shows a marginally better position in school dropouts (12.7%) compared to Hindus (15.8%), and enrolments with

83.4% and 81.5% respectively. The better performance of the Muslim community follows the complaints from the Assamese non-upper[M7] Muslim community that its mother tongue is often different from that in local Assamese medium schools. Perhaps the Muslim community is catching up fast in terms of literacy and school enrolments. There are problems with the data relating to higher education but one can see, at least as far as school education is concerned, that the Muslim community is actually better off than the Hindu community in Assam.

52

Table 49: Literacy Rate in Assam MCDs (%) District Hindu Muslim- SC & ST OBC GC* Total General Kamrup 77.6 77.6 82.7 78.9 73.6 Barpeta 76.3 81.7 90.4 84.1 68.3 Darrang 73.2 76.3 78.9 75.8 68.2 Marigaon 75.4 89.2 81.4 79.2 72.7 Kokrajhar 66.6 65.0 67.0 66.5 58.2 Bongaigaon 68.1 78.1 83.5 73.2 65.8 Dhubri 70.1 73.5 79.3 72.9 64.7 Nagaon 77.1 71.8 87.1 76.5 72.1 Gopalpara 79.5 79.7 84.4 80.5 63.2 Hailakandi 88.8 85.8 89.7 88.0 86.2 Cachar 81.0 88.8 96.1 86.7 87.7 N.C. Hills 87.2 97.3 98.4 88.2 Karimganj 91.6 95.4 97.3 94.4 83.0 Average 78.2 81.1 85.4 80.4 71.8 *General category

Figure 12: Literacy Rate Across Hindu-Muslim Communities in Assam MCDs Karimganj, 94.4 100 80.4 Kokrajhar, 66.5 80 Hailakandi, 87.7 60 40 Kokrajhar, 58.2

20

0 Lowest Average Highest All Hindu Muslim-General

Occupational Pattern, Assets and Income

The position of agricultural assets in terms of landlessness presents extreme variation, not so much in terms of inter-community differences as in inter-district variations across the

MCDs in Assam. There is absolutely no landlessness among either of the communities in

Gopalpara district, whereas it is extremely high in Cachar where 76.1% of Hindu and 77.6% of

Muslim households do not possess any land. Unlike in the other states, landlessness in Assam is not only low but the differences between the Hindu and Muslim households are also marginal.

In fact, landlessness is higher among Hindus than Muslim households in Karimganj, Hailakandi,

Nagaon and Kamrup (Annexure 37). Obviously, the Muslim community in Assam is also substantially dependent on agriculture. This is clear from the fact that there is no difference between landlessness of Hindu-General and Muslim-General (Table 50). The position of

SCs/STs is also better than these two communities.

As a whole, for all communities, the single largest source of employment in the MCDs of

Assam is agriculture and allied activities, though its share is less for Muslims (44.5%) than for the

53

Hindus (50.5%) (Annexure 38). There are some regional exceptions. Interestingly, agriculture accounts for the lowest share of employment for both Muslims and Hindus in a couple of districts viz. Karimganj (Hindus 17.2% and Muslims 21.4%) and Cachar (Hindus 24.4% and

Muslims 26.4%). In Gopalpara too both the communities show lower agricultural dependence

(Hindus 36.2% and Muslims 38.6%). Kamarup is at the other end of the spectrum, with both highest agricultural dependence for both Hindu (73.4%) and Muslim (69.9%) workforce (Table

51). Among the Hindus, the dependence on agriculture is the highest (55%) among SCs/STs.

Table 50: Caste/ Community-wise Landlessness in Assam MCDs Caste / Community Percentage of Landless Households Average for MCDs Lowest / District Highest / District Hindu-General 29.5 0.0 85.2 (Gopalpara) (Cachar) Hindu-OBC 36.3 0.0 73.0 (Gopalpara) (Cachar) Hindu-SC/ST 23.0 0.0 75.7 (Gopalpara) (Cachar) Muslim-General 29.4 0.0 77.6 (Gopalpara) (Cachar)

Table 51: Caste/Community-wise Employment in Agriculture and Allied Activities in Assam MCDs Caste / Community % Share of Employment in Agriculture and Allied Activities Average for MCDs Lowest / District Highest / District Hindu-General 41.2 3.6 68.2 (Dhubri) (Kamrup) Hindu-OBC 48.8 20.1 75.1 (Karimganj) (Kamrup) Hindu-SC/ST 54.6 19.9 75.2 (Karimganj) (Kamrup) Muslim-General 44.5 21.4 69.9 (Karimganj) (Kamrup)

The share of employment in the secondary sector is relatively low for both the communities but it is much lower for Hindus (17.3%) than for the Muslims (21.8%) (Figure 13).

Even for Muslims, there are only two districts viz., Cachar (35.1%) and Kokrajhar (32.3%) where secondary sector employment is close to about one-third of total employment. The agriculturally dominant Kamarup accounts for lowest secondary sector employment for both Hindus (11.8%) and Muslims (13.0%) (Annexure 39). Darrang is another district where the secondary sector offers relatively low extent of employment for both the communities.

Figure 13: Secondary Sector Employment in Assam MCDs

40 Kokrajhar 35 , 35.9 30 21.8 25 Kokrajhar, 32.3 20 Darrang , 13.2 17.3 15 Darrang, 11.8 10 5 0

% Employed in Secondary Sector Lowest Average Highest All Hindu Muslim-General 54

Employment in the services sector accounts for almost one-third share for both Hindus

(32.1%) and Muslims (33.7%) in MCDs of Assam as a whole. Interestingly, Karimganj presents a picture of dominance of the service economy, with the majority of the Hindu (58.1%) and

Muslim (52.3%) workforce employed in the tertiary sector. In Barpeta and Cachar also about

50% of the Hindu workforce is employed in the tertiary sector (Annexure 40). Of course the case of the N.C. Hills is exceptional, with the entire Muslim workforce in tertiary sector.

Obviously the presence of Muslim population in the district is also very meager. Unlike considerable occupational differences between the Hindu and Muslim households in the MCDs in other states, in Assam agriculture and services are the main sources of employment for both the communities, with relatively low level of secondary sector employment, except ni Kokrajhar and Cachar where about one-third of the Muslim workforce is in the secondary sector.

Employment in the service sector in Assam does provide a certain reflection of caste / community hierarchy with 40.5% the Hindus-General, 35.4% of Hindu-OBC and only 27.7% of

SC/ST workforce in services. 33.7% Muslim-General workers are in services (Table 52). It would have been more interesting to see any intra-sectoral variations between the communities; for instance, how much of service sector employment is in petty trade and business and how much in public and business services. However, lack of even two-digit level data is a big constraint to looking closely at the possible occupational differences within the broad sectoral classifications.

Table 52: Caste /Tribe/Community-wise Employment in Tertiary Sector in Assam MCDs Caste / Community % of Employment in Tertiary Sector Average for MCDs Lowest / District Highest / District Hindu-General 40.5 14.5 69.0 (Kamrup) (Cachar) Hindu-OBC 35.4 13.3 60.4 (Kamrup) (Karimganj) Hindu-SC/ST 27.7 16.1 51.6 (Kamrup) (Karimganj) Muslim-General 33.7 17.1 100.0 (Kamrup) (N.C. Hills)

Indebtedness

55

Overall, in the MCDs of Assam, the incidence of indebtedness is relatively low for both

Hindus (15.7%) and Muslims (19.7%). It is not possible to say from the findings as to what extent the low indebtedness is due to poor banking facilities and lack of financial inclusion, which are often mentioned as one of the problems in the North-Eastern States. But in three districts viz., Darrang, Marigaon and Kokrajhar, the incidence among Muslim households is more than double that of the Hindu households (Annexure 41). With the meager data available, it is also not possible to explain how it could be just 5% or below for both the communities in as many as four districts viz., Karimganj, Hailakandi, Gopalpara and Cachar; and in Hailakandi, the less than one per cent incidence of household indebtedness is also coterminous with the entire debt of Muslim households being met through formal sources. But for all the districts together, even with low incidence of indebtedness the formal sources account for only 31.3% for Hindu households and 20.6% for the Muslims (Annexure 42). Even with low levels of indebtedness, formal institutional sources appear to work better for Hindu-General than for SC/ST and

Muslim communities (Table 53). It would be interesting to see how Cachar, Karimganj and

Hailakandi were able to meet all their credit needs through formal institutions. Still, for SCs/STs even the best district could meet only 50% of the credit needs through formal sources.

Table 53: Caste /Tribe/ Community-wise Formal Sources of Credit in Assam MCDs Caste / Community % Share of Formal Institutional Sources in the Household Indebtedness Average for MCDs Lowest / District Highest / District Hindu-General 38.0 10.0 100 (Kokrajhar) (Cachar) Hindu-OBC 31.4 10.5 100 (Nagaon) (Karimganj) Hindu-SC/ST 27.0 13.3 50 (Nagaon) (Gopalpara) Muslim -General 20.6 7.2 100 (Darrang-Marigaon) (Hailakandi)

Access to Basic Amenities

Another distinguishing feature of Assam MCDs, unlike UP, Bihar and West Bengal, is the relatively better performance of the Public Distribution System. What is interesting is the relatively very high level of access to the PDS for both Hindu (75.5%) and Muslim (73.5%) 56 households. Except for one district Hailakandi (48.3%), in all other districts, the PDS is accessed by more than half of the Hindu households. It is similar for Muslim households, except in

Darrang (44.4%), Marigaon (44.4%) and Hailakandi (47.8%) (Annexure 43). What emerges from

Table 54 is that the PDS in Assam is not only accessible to almost three-fourths of the rural households but also that the access is fairly equal among all the communities, without much discrimination. It would also useful to probe further as to what makes Kokrajhar and N.C. Hills reach almost all households, and to see why Hailakandi turns out to be a low performer in PDS in an otherwise reasonably fair picture of overall PDS performance in the MCDs.

Table 54: Access to Public Distribution System in Assam MCDs Caste / Community % of Households with Access to PDS Average for MCDs Lowest / District Highest / District Hindu-General 77.3 53.2 95.2 (Hailakandi) (Kakrajhar) Hindu-OBC 72.6 42.6 93.8 (Hailakandi) (N.C. Hills) Hindu-SC/ST 76.3 50.0 94.8 (Hailakandi) (N.C. Hills) Muslim-General 73.5 44.4 89.3 (Darrang / Marigaon) (Kakrajhar)

The situation regarding housing, by the existing definition of ‘pucca walls’, is a cause for concern in MCDs in Assam: Only 9.2% of Hindu and 5% of Muslim households have pucca houses by this definition. There is a need to be skeptical about this culture-climate-neutral definition. However, given this definition, the housing deficit is poor for both, but much more so for the Muslim community. In no other indicator discussed so far is the intra-community difference as much as in the case of housing (Annexure 44). There do exist differences that coincide with the caste / community hierarchy but that is within a low level that ranges from

7.3% for SCs/STs to 14.8% for Hindus. Of course among Muslims-General, it is much less at

5%.

In terms of drinking water connectivity, the position of the Muslim community is much better (59.3%) compared to the Hindus (50.0%). The situation for both communities is dismal in Karimganj (Hindus 19.1% and Muslims 9.9%) and Hailakandi (Hindus 7.6% and Muslims

9.1%) as can be seen from Annexure 45. What is worse is that in a state like Assam with high

57 rainfall and rich ravine resources, there could be such a high deficit in access to safe drinking water. How much is because of a problem in problem and how much is real is not clear from the reports.

The situation of in-house toilet facilities appears to be much better with almost half the households reporting having the amenity, though it is marginally higher for Hindu households

(53%) compared to 47% for Muslim households (Annexure 46). What is interesting is that almost all households (96% to 98%) from both communities reported having in-house toilet facilities in Hailakandi and Karimganj, where we observed that hardly one-tenth of the households of both the communities have in-house drinking water access! In the case of drinking water and W.C. toilet facilities, though there are not much inter-community difference, there are very wide inter-regional variations in Assam. It would be interesting to incorporate climatic and geographical aspects as well as cultural differences to understand the reality.

The real shock is in the case of the household electricity connections. Here, it is not geography but tribe / community that seem to account for disparities. The connectivity is low and the intra-community disparity is high. Only 30% of Hindu households have pow er connections, but just half of that (15%) for the Muslims. The worst situation for the minority community is in Gopalapara (5%) and Barpeta (7%) districts (Annexure 47). Even at the low level of overall availability of electricity, there is a clear hierarchy of access reflected in the caste / tribe / communal differences with 39% of the Hindu-General, only 25% of SCs/STs and just

15% of Muslim-General households with power. For Hindus-General the connectivity ranges from 18 to 61% but for SCs/STs it ranges from 1 to 41%, and for Muslims-General from 5 to

29 %(Table 54A).

Table 54A: Caste / Tribe/ Community-wise Households with Electricity in Assam MCDs Caste / Community % of Households with Electricity Average for MCDs Lowest / District Highest / District Hindu-General 39 18 61 (Darrang) (Barpeta) Hindu-OBC 28 14 63 (Darrang / Barpeta) (N.C. Hills) Hindu-SC/ST 25 1.0 41

58

(Dhubri) (N.C. Hills) Muslim-General 15 5 29 (Gopalpara) (Kamrup)

5.3 Orissa

Orissa is the most backward of all the larger states in the country. The share of the ST population is one of the highest in the country. , newly carved out in 1992 from

Ganjam, is the only MCD in Orissa. It is a category ‘A’ MCD, which means it suffers from deficit in the socio -economic indicators as well as basic amenities. The survey report is very elementary.* Though the Christian minority constitutes 33.47% of the population, the district is substantially inhabited by STs about which we hardly have any details. The mere division of the population into Christian and non-Christian categories does not help in providing information about the socio -economic and cultural landscape of the district.

Literacy and educational levels do not show much difference between Christian and non-

Christian communities, and it is dismal at about 56% for males and 43% for females. Proportion of children not attending school is as high as 17% for Christians and 9% for non-Christians.

Apparently there are wide variations across the villages surveyed but no explanation as to what contributes to such extreme variation within a district. For instance, male literacy varies from

13% in one village (Lumundasing) to 94.81% in another (Khurigaon), and similar variations exist in the range of female literacy from 12% to 68%. Interestingly, a higher proportion (68%) of non-Christians is close to that higher figure. What is puzzling is that 90% of Christians and 78% of non-Christians report non-institutional child deliveries, i.e. child birth at home. But state- aided immunization is reported as high as 98%, for both the communities.

Though the report does not give any estimates of work participation rate, agriculture (no indication whether this is podu or shifting agriculture) appears to be the main occupatio n.

* It does not even provide religion-wise distribution of population except starting off with the statement that it is a minority district with 33.47% of the population being Christian. The rest of the population is treated as ‘non- Christian’ for the entire analysis. We do not even get any account of the proportion of ST population, nor an inkling that most of the ‘Christians’ are indeed ST population 59

However, what is striking is the incidence of migration to destinations outside the state is as high as 58% for Christians and 60% for non-Christians.

The figures reported for certain amenities challenge intuitive understanding. Though only 32% of Christian and 23% of non-Christian households report having domestic electricity connection, 87% of Christians and 81% of non-Christian households report possessing septic tank latrines or water sealed latrines in house. There is hardly any household among both the communities with tap water connections and most of them depend on either public wells or public hand pumps within a distance of less than one kilometre. Most of them live in kutcha or semi-pucca houses and only 6% of Christians and 18% of non-Christians have pucca houses.

Housing provided by the government accounts for only 5% of households in both the communities.

VI

North Eastern States

Assam is included in the Eastern region because of the similarity to West Bengal in the nature of the primary minority religious group viz. Muslims. Five states are included in the

North East viz. Arunachal Pradesh (7), . Manipur (6), Meghalaya (1), Mizoram (2) and Sikkim

(1). These states together account for the third largest number of MCDs (17).

6.1 Arunachal Pradesh

Arunachal Pradesh is vast, much of it remote, but with over one thousand kilometres of international border, the state is culturally as important as it is strategically. The sparse population with a density of 13 per sq.km., and vast diversity of culturally rich ST groups along with internationally somewhat porous borders, makes Arunachal Pradesh a cultural and political melting pot. As many as seven of its districts are identified as MCDs. Four of these districts viz.

East Kameng, Lower Sabhansri, Changlang and Tirap are category ‘A’ MCDs which lag behind 60

both in socio-economic indicators and in basic amenities. The other three viz. Tawang, West

Kameng and Paum Parc are category ‘B’, that lag in socio-economic indicators. Though there

are several religions, more 75% of the State’s population belongs to STs. Scheduled Tribes are

spread across all religious groups except Muslims. Besides Christianity and Buddhism which are

the two major minority religions in the State, there is a substantial population which is referred to

as belonging to ‘other’ religious faiths. For instance, as much as 64% of the population of Lower

Subhansri is referred to as belonging to ‘other’ religions. There is also an active process of

conversion to Christianity in many parts. The high growth of population also suggests that there

has been large influx of people from Bangladesh, and Tibet.

In five of the MCDs, Buddhism is the main minority religion, while in two others

Christianity is the main minority religion. The religion-wise analysis in the survey reports several

limitations because of sample design. For instance, in the case of Tawang, of the total sample

households of 636, Hindu households were only 3 and the remaining 99.5% were Buddhists. In

the case of West Kameng, out of the total sample households of 740, Christians and Muslims

represent only six households each. These thin samples could have been dropped from

comparative analysis. There also problems of non-comparability across many of the religious

faiths. For all these reasons, only the data on development indicators as presented in the reports

are produced here (Table 55).

Table 55: Summary Statement of Development Deficits in MCDs of Arunachal Pradesh (%) Indicators East Lower Changlang Tirap Tawang West Paun Kumang Subhansiri Kemang Parc Socio-Economic 1. Rate of Literacy 75.77 70.04 71.40 51.0 61.08 (4)[M8] (4) (4) (3) (3) 2. Rate of Female Literacy 69.88 63.29 64.00 72.50 55.00 (4) 3. Work Participation Rate 60.40 71.36 45.00 44.51 72.82 4. Female Work Participation Rate 42.57 64.86 38.00 23.03 60.51 (4) Basic Amenities 5. Pucca Houses 3.54 14.88 1.20 18.10 32.03 (1) (1) (1) (1) (1) 6. Households with Access to Safe 95.61 73.99 60.0 24.0 96.22 Drinking Water (3) (3) (3) (2) 7. Households with sanitary 8.21 3.47 0.30 89.80 18.24 facilities (2) (2) (2) (2) 8. Households with Electricity 94.62 77.60 84.40 100 96.00 Health Indicators 9. Fully Vaccinated Children 56.09 98.8 64.30 77.50 84.65 10. Institutional Deliveries 5.53 35.15 7.30 10.50 25.10

61

6.2 Manipur

There as many as six districts identified as MCDs in Manipur. Except , which is identified as an ‘A’ category district that suffers from deficits in both socio -economic indicators and amenities, the remaining five districts are in the B2 category, lacking in amenities indicators.

Besides Thoubal, the five districts are , Tamearglong, , and

Chandel. Except in Thoubal where Muslims constitute about 25% of the population, the minorities in all other districts are Christians, and almost all Christians are comprised of tribal population. Again, there is need to caution that most of the tribes of North East are not comparable to those in the Indian mainland like Orissa, Chattishgarh or Andhra Pradesh.

Apparently these tribes may be practicing Jhum cultivation yet could be highly literate and politically more autonomous. Most of these districts are characterized by the Autonomous

Tribal Councils with legislative powers on a number of traditional practices and rights. For instance, Chandel is an MCD in Manipur which is very sparsely populated with a predominantly

Christian population comprising of 20 tribes, but with a literacy level of 92%.

The major problem in detailed analysis of MCDs in Manipur relates to the sample design and actual execution. For instance, has population comprising of about 20% of

Hindus and 78% of Christians, but the total sample of 723 households comprises of just 13

Hindu households (1.8%), the remaining 710 households (98.2%) being from the Christian community. Similarly, for Chandel, out of a total sample of 704 households, 702 are Christians and only 2 are Hindus. In the case of Thoubal, the population comprises of 61% Hindu, 24%

Muslim, 1.4% Christian and about 15% ‘others’. There is no explanation of either the others or the explanation of the composition of the sample. There are hints that severe problems were faced because of security and insurgency reason in conducting surveys in these districts. A detailed analysis is possible only when the data limitations are spelt out.

62

6.3 Meghalaya

Meghalaya is a multi-ethnic society. West Garo Hills is the only MCD identified in the state. In the West Garo Hills, Christians with 54.57% constitute the majority of population followed by Hindus (21.5%) and Muslims (15.23%). The sample households show over representation of Christians constituting 72.7%, followed by Hindus (14.5%), Others (8.8%) and

Muslims (4%). While almost all Hindus, Christians and Others in the sample households are classified as STs, all Muslim households belong to the ‘General’ category.

The estimated literacy rate among Hindus is 60.6%, and it is 63% among Muslims, 74% among Christians, and 48% among ‘Others’.* Though Meghalaya is known for its matriarchal social structure, the female work participation reported is very low for all groups: Christians

(12%), Muslims (7%), Hindus (14%) and ‘Others’ (11%). The majority of Hindus (65%),

Christians (63%) and ‘Others’ (84%) are occupied in farming, but only 43% of Muslims are engaged in agriculture. The majority of Muslims are in non-agricultural occupations. This is also reflected in the high level of landlessness among Muslims, while most of the Hindus, Christians and ‘Others’ own land. Most of the Christian households possessed livestock while it was very exceptional among Muslims. Though no clear picture emerges from the report on the proportion of households from different religious groups migrating, it does reveal interesting religious patterns among those who migrate. First, migration among Christian households is mostly from rural to urban areas and much of it is long term migration. In contrast, migration among Hindu and Muslim households is mostly rural to rural short duration migration. Second, there is very little migration outside the state among Christians and it is also very low among

Hindus (5%); but among Muslim households migration outside the state is 22%.

The housing status reveals that about 17% of Muslims do not have their own housing but live in rented houses, while almost all Christians, Hindus and ‘Others’ have their own houses.

* However, there are serious problems with the data as presented in the report on West Garo Hills, and this applies not only to literacy but most of the other aspects as well. 63

All Muslims live in kutcha houses while about 22% of Hindus and about 5% of Christians and

‘Others’ have semi pucca or pucca houses. Domestic electricity connectivity is in a poor state especially for Muslims (only 18% have electricity connection) and ‘others’ (8%). Hindu and

Christian households are relatively better off with 48% and 30% connectivity respectively.

Interestingly, a majority of Muslim households (63%) have their own source of water, while all others depend on different protected and unprotected sources of water. The status in terms of better toilet facilities is similarly in the case of Muslims compared to other communities. Thus,

Muslim households appear to pay more attention to ensuring better water and domestic sanitation facilities, although even among them it is a long way from all households having these facilities. Though there are serious deficiencies in full immunization, the condition of Muslim and Christian children (30%) is much better than the Hindu children (15%). But Muslim households lag far behind in accessing the public distribution system (PDS) with only 5% able to access the facility compared to 67% for Christians and 22% for Hindus.

The villages surveyed record widespread discontent regarding electricity connectivity, public drinking water supply and communication facilities.

6.4 Mizoram

The population of Mizoram consists of predominantly STs who constitute 96.3% of the state’s population. Most of the STs belong to the Christian faith which accounts for 81% of the state’s population. Thus, Mizoram is a state where the otherwise minority Christianity is the majority religion. The minorities in Mizoram are Buddhists (15.5%), Hindus (2.3%), and

Muslims (0.7%) who together constitute 19% of the population. The two districts identified as

MCDs are Lawngtlai and Mamit, both selected in the B2 category, meaning that these districts have amenities deficits and not deficits in terms of socio-economic indicators like literacy and work participation. In Lawngtlai, ‘minorities’ include Hindus (2.6%), Muslims (0.3%) and

Buddhists (52.17%) who together account for 55% of the population, whereas Christians, the

64

state’s major religious group, constitute 44.66%. In Mamit, minorities include Hindus (4.3%),

Muslims (1.8%) and Buddhists (16.44%) who together account for 22.54% of the population of

the district. In view of the complexity involved in treating a national minority religion as a

majority religion and treating other religions as minorities, and in view of misleading sample

design in Mamit where the major minority viz. Buddhists (there may be reasons of difficult

reach) is totally excluded from the sample, the following Table 56 attempts to provide a certain

mapping of the community-wise distribution of population and the sample households. In the

sample design in the case of Lawngtlai, the ‘minority’ Hindu is left out and other ‘minority’

Buddhist is under represented. In the case of Mamit, exclusion of the major minority Buddhisst

would disqualify the whole exercise from the MCD survey. Further, a thin sample of 4 Muslim

households in the total of 551 households in Lawngtlai, and equally thin 5 Hindu and 11 Muslim

households in a total sample of 625 households in Mamit makes interpretation of the data from

any of these households meaningless.

Table 56: Community-wise Distribution of Population and Sample Households in MCDs of Mizoram (%) District / State Hindu Muslim Christian Buddhist ST 1. Lawngtlai 2.6 0.3 44.66 52.17 95.4 (100/551) (0/0) (0.73/4) (78.95/435) (20.33/112) - 2. Mamit 4.3 1.8 77.21 16.44 94.9 (100/625) (0.8/5) (1.76/11) (97.44/609) (0/0) - Mizoram 2.3 0.7 81.01 15.50 96.3 NB: Figures in parentheses refer to percentage distribution of sample households.

It is very difficult to interpret the results presented in Table 57 because the Buddhists

and Christians there are essentially tribal communities living in remote areas, with distinct

cultural traits, whereas Hindus and Muslims may be migrants/ settlers from outside the state or

country. Further, as mentioned above, the four and five households representing Muslims and

Hindus in the two districts respectively make the results relating to them highly unreliable and

misleading. One would expect that electricity would be a problem in remote areas, but of all the

amenities, electricity appears to be better provided, and the situation relating to all other

amenities is dismal for all communities. The high presence of Hindu and Muslim cultivators

only raises questions about the origin of these communities and about more issues like in-

migration and encroachments!

65

Table 57: Demographic, Social and Amenities Position of MCDs in Mizoram (%)[M9]* Indicator Lawngtlai Mamit Muslim Christian Buddhist Hindu Muslim Christian 1. Size of Hh. 5 5 5.21 5 5.56 5 2. Dependency Ratio 0.47 0.96 0.60 0.64 0.81 0.69 3. Sex Ratio 923 980 927 923 964 1018 4. Literacy Rate 93.33 78.49 68.22 61 84 92 5. Never Enrolled 0 5 6 14 14 7 6. Pucca House 0 1.61 4.46 0 0 6 7. Electricity 75 49 48 80 55 79 8. InHouse Water 0 10 4 0 18 4 9. In-House Toilet 0 9 16 20 0 18 10. Work Participation Rate 49 53 52 61 59 64 11. Cultivators 50 38 36 71 88 59 12. Agricultural Labourers 38 50 37 29 4 27 *Figures in % for indicators 4 to 12

6.5 Sikkim

Sikkim is one of the smallest states of India in terms of population. Though Hindus are

in majority, Buddhism and Christianity are the other important religions in the state. North

Sikkim is the only MCD in the state. It is identified as being in the B2 category, which means its

deficits are in amenities. North Sikkim has a Buddhist population of 55%. There are problems

with the analysis of the report which is presented in terms of only two categories viz. Buddhist

and non-Buddhist.

North Sikkim is a sparsely populated district with the large northern part of the district

being uninhabited. It is an agricultural district with cardamom as the main crop. Tourism is the

most important economic activity and source of livelihood for the majority of the population.

Literacy levels for both Buddhists and non-Buddhists are very high at over 80% for males and

females, though males have a marginally higher rate. School enrolment rates are almost 100%

for both groups, and most of the schools are government or aided schools. About 50% of

Buddhists and non-Buddhists have access to schools within one kilometre of their residence but

in other cases the distance is more, largely because of the terrain and sparse population.

Interestingly, the medium of instruction is English for 86% of Buddhists and 77% of non-

Buddhists. Regular mid-day meals, free books and regular and disciplined teachers are common

features of the education facilities accessed by both the communities. Equally positive aspects

are noticed in the case of health facilities: 92% of Buddhists and 95% of non-Buddhists access

66 health facilities provided by the government and dependence on private facilities is much less.

Majority of child deliveries are in public hospitals though in the case of both Buddhists and non-

Buddhists, deliveries at home are still 47% and 48% respectively. The immunization record too is almost 100% for both the communities and these services are provided almost entirely by the government.

Access to basic amenities is highly satisfactory, except for housing in the case of non-

Buddhists. While 95% of Buddhists have their own housing, 28% of non-Buddhists live in rented houses. Of course pucca houses are available to only 31% of Buddhists and 17% of non-

Buddhists. The condition relating to electricity connectivity excels compared to most of the

MCDs, with 95% of Buddhist and 92% of non-Buddhist households having connectivity.

Similar is the case relating to toilet facilities with 94% of Buddhists and 96% of non-Buddhists with in-house toilet facilities. Tap water is available in about 37% of households of both the groups but there is m ore dependence on natural sources like ponds, streams or rivers.

Though there are problems with the way in which occupational classification* is done in the survey report; agriculture appears to be major occupation for both the groups but more so for Buddhists than non-Buddhists. Migration appears to be very high but migration for work with migration for studies is not separated. There is of course large scale migration for educational purposes among both Buddhists and non-Buddhists. Non-agricultural activities including business and financial services are very low. Service sector employment is confined to government jobs, but what is puzzling is that despite such high levels of public education and health facilities, the survey reports low levels of awareness.[M10] The low participation in

NREGS may be because of its inappropriateness in the context of better educational levels and aspirations. The incidence of indebtedness is almost negligible (3% to 4%) for both the groups.

The PDS is accessed by 69% of Buddhists and 72% of non-Buddhists, although there are

* There is no differentiation made between worker and non-worker, work participation and domestic work or study. This was noticed in several other MCD reports prepared by the institution which prepared the North Sikkim report. 67 problems of insufficiency of quantity supplied or lack of adequate resources to buy all rations in the case of some households.

VII

Other States

There are nine MCDs which do not easily fall in any regional contiguity. These are across five states viz. Maharashtra (4), Madhya Pradesh (1), Karnataka (2), Kerala (1) and

Andaman and Nicobar Islands (1). There is very little comparability of these MCDs either within the region or across the regions. Except the two in Karnataka, many of them have sort of stand along characteristics to the state they belong.

7.1 Maharashtra

Four districts are identified in Maharashtra as MCDs. In none of these districts do minorities exceed 25%. In all these districts the largest minority religion is Buddhism and in these four districts the Buddhist population ranges from 9% to 16% only. Interestingly,

Maharashtra has the fourth largest concentration of Muslim population in the country. It may be that there are no development deficits in the districts where Muslims are concentrated and hence the absence of such districts in MCDs of the state. Of the four districts, Parbhani is included under category A, which means deficits in both socio-economic and amenities ind icators. The other three districts, Buldhana, Washim and Hingoli are included in category B2 which means deficits in amenities.

Table 58 gives district and religion-wise distribution of population in these districts. The figures in parentheses show the sample distribution, in which minorities are in a higher proportion to capture adequate number of households. For instance, in Parbhani both

Buddhists (9%) and Muslims (7%) account for only 16%. But what is not made clear is that the

Buddhist population shown in these districts is entirely ‘Neo Buddhists’ who are entirely

68

converts from Dalit communities. Neo Buddhists are officially treated as SC/ST. They are not

comparable to Buddhists elsewhere, and the comparable group is the SC/ST population. It is

well recognized that in general, the condition of minorities like Muslims is better than that of

SC/ST communities, but worse than the General category of the Hindu population. Though the

four reports do not provide analysis differentiating social groups within the religious groups, the

results tabulated here on certain select characteristics like literacy, employment pattern, and basic

amenities do reveal the deficits of the Buddhist group compared to others.

Table 58: Community-wise Population Distribution of MCDs in Maharashtra (2001 Census) (%) District Hindu Muslim Buddhist Total Minorities 1. Parbhani 83.72 6.64 9.36 16.28 (68) (11) (21) (32) 2. Buldhana 75.3 9.1 15.1 24.6 (67) (15) (17) (32) 3. Washim 76.81 6.49 16.16 23.19 (67) (9.2) (23) (33) 4. Hingoli 77.62 6.11 15.81 22.38 (68) (5.56) (25.67) (32) NB: Figures in parentheses refer to percentage distribution of sample households.

The following Tables 59 and 60 suggest that in literacy, the Hindu community does

marginally better than the Muslims, and the Buddhists are on par with them. But in the ‘never

enrolled’ category, the Muslim community shows a much higher level even compared to

Buddhists, at least in three of the four districts. However, that the Buddhist community is much

poorer and suffers higher development deficits is revealed in its poor access to basic amenities.

Except in domestic electricity connectivity and in the case of in-house toilets in two districts,

Muslims lag behind the Hindu households; but Buddhists lag behind all communities in almost

all amenities, except a few exceptions like access to water in Washim.

Table 59: Literacy and School Enrolment Status in MCDs in Maharashtra (%) District Hindu Muslim Buddhist 1. Parbhani 70 68 66 2. Buldhana 78 77 75 3. Washim 74 70 73 4. Hingoli 74 64 68 Never Enrolled (%) (6-16 years) 1. Parbhani 3 4 6 2. Buldhana 9 10 4 3. Washim 7 18 5 4. Hingoli 4 8 4

69

Table 60: Access to Basic Amenities MCDs of Maharashtra (%) District Hindu Muslim Buddhist 1. Pucca House Parbhani 24 14 9 Buldhana 16 13 8 Washim 17 8 9 Hingoli 19 8 8 2. Electricity Parbhani 68 67 47 Buldhana 66 76 50 Washim 66 69 57 Hingoli 76 66 48 3. In-House Water Parbhani 21 19 3 Buldhana 19 17 8 Washim 19 2 13 Hingoli 26 14 10 4. In-House Toilet Parbhani 6 4 5 Buldhana 17 22 8 Washim 20 19 11 Hingoli 18 22 7

7.2 Madhya Pradesh

The focus of MCD surveys is on rural areas and the sample unit is the villages in the

selected districts. But certain exceptions are made to this rule and one such is ,

which is predominantly urban. 73% of the population in Bhopal is Hindu, 23% Muslim and

others constitute the rest. The sample households for the survey are drawn from both urban and

rural areas of the district. This report adopts a totally different approach by dividing the district

into the following three categories:

Category I: Localities with minority concentration 0 to 25% Category II: Localities with minority concentration 26 to 75% Category III: Localities with minority concentration >75%

Table 61 shows the position of households in terms of key socio -economic and amenity

indicators. The regional categories presented do not indicate any clear differentiable patterns.

The classification of work in the report is such that it does not reveal any picture on employment

status or sectoral distribution. However, one may venture to observe that the overall conditions

appear to be better in the case of Category I where minorities are less than 25% and in Category

III where minorities are more than 75%. Category II with a highly mixed population seems to

be lagging behind.

Table 61: Key Socio-Economic and Amenities Indicators Relating to Households in Different Categories in Bhopal (%)

70

Indicator Category I Category II Category III 1. Literacy Male 85 73 75 Female 70 64 64 Persons 78 68 70 2. Government Schools 71 39 40 3. Medium in Schools Hindi 83 71 34 English 7 25 34 Urdu 0 1 9 Hindi / English 9 4 24 4. Housing Semi Pucca / Pucca 52 48 68 Rented / Temporary Settlement 20 47 0 5. Drinking Water Tap Water 68 56 87 6. Electricity Connection 79 93 97 7. In-House Toilet 51 57 93

7.3 Karnataka

Bidar and Gulbarga are the districts identified as MCDs in Karnataka. Both are in the B1

category, which means these districts suffer deficits in socio-economic indicators and not in

amenities. Bidar is one of the backward districts in the dry and drought prone North Karnataka.

The main minority community is Muslim, accounting for about 20% of the district population.

Other minorities like Christians constitute a little less than 3%, the remaining 77% are Hindus.

The district also has a very high concentration of SC (20%) and ST (12%) population together

accounting for 32%. To that extent all the indicators of the Hindu community reflect the

presence of this SC and ST concentration.

Gulbarga too is a part of the dry drought prone region of North Karnataka. Muslims

constitute 18% of the total population of the district, though their share ni rural population is

only 12%. The proportion of SCs is also relatively high at 25%.

Table 62 shows that both the districts have very low rates of literacy, and a high

proportion of ‘never enrolled’ children in the age group of 6-16 years. More than lo w literacy,

the latter is a matter of serious concern because it impacts on the quality human resources for

the future. Except in electricity connectivity, in all other amenities like pucca housing, in-house

water facilities, and in-house toilets, both the districts are in a poor state. And in the case of

71 most of the indicators, except sex-ratio, the Muslim community suffers more serious deficits than the Hindus.

Table 62: Demographic, Social and Amenities Position in MCDs in Karnataka (%)[M11]* Indicators Bi dar Gulbarga Hindu Muslim Hindu Muslim 1. Average Family Size 5.8 7.0 6.15 6.91 2. Dependency Ratio 0.60 0.83 0.62 0.80 3. Sex Ratio 862 876 901 946 4. Literacy Rate 61 61 52 50 5. Never Enrolled (6-16 years) 18 24 18 22 6. Pucca House 8 3 12 11 7. Electricity 89 88 91 90 8. In-House Water 19 5 12 8 9. In-House Toilet 7 7 4 2 10. Landlessness 26 34 22 29 11. Institutional Deliveries - - 24 21 12. Partial Immunization 69 65 93 94 13. Incidence of Migration 17 20 16 23 *Figures in % for indicators 4 - 13 The high level of backwardness of these districts is reflected in the heavy concentration of labour force in dry land low productivity agriculture. For 74% to 79% of the Hindu workforce and 66% to 74% of the Muslim workforce, agriculture is the main occupation, with construction with 9% providing the next important occupation for both Hindus and Muslims in

Gulbarga, and petty trade and hotels in Bidar. There is a relatively high incidence of migration with 16% to 17% of Hindus and 20% to 23% of Muslim households reporting at least one migrant. Much of the migration is also casual but at a long distance outside the state. The higher proportion of Muslim migration is also an indication of their relatively lower economic position in these districts.

7.4 Kerala

Although minorities constitute 45% (25% Muslim and 20% Christian) of Kerala’s population, Wayanad is the only MCD identified for survey under the B2 category. In other words, it is an MCD not because of deficits in socio -economic indicators like education and work participation but because of amenities like housing, drinking water, electricity connectivity and toilet facilities. Wayanad is a hilly district and predominantly rural (96%), but rich in plantations like tea, coffee, pepper and rubber.

72

The population of Wayanad consists of 50% Hindus, 27% Muslims and 23% Christians.

Most of the ST population of Kerala is concentrated in Wayanad. STs constitute about 18% and

are treated as part of the majority community viz. Hindus. SCs constitute only 4% of the

population. Work participation in the district is relatively high at about 40% (33% Kerala) and

the major occupation is agriculture.

The survey results show (Table 63) relatively high sex ratio, (except for Christians), very

low evelsl of dependency and relatively smaller size of households (except for Muslims). Literacy

levels are very high ranging from 88% for Hindus (in spite of 36% of Hindus being STs) to 98%

for Christians. The male-female difference in literacy is marginal. Work participation among

male Muslims (51%) and male Hindus (50%) is high, though it is only 43% for male Christians.

The overall female work participation is lower (16%) and it is lowest at 13% for Muslim women.

Table 63: Demographic Features of Households Surveyed Across Religious Communities in Wayanad Community Dependency Sex Ratio Size of Literacy (%) Ratio Household (7 and above) Male Female All Hindu 0.43 1008 4.51 89 87 88 Muslim 0.46 1060 5.40 95 91 93 Christian 0.50 985 4.67 99 97 98 All 0.46 1025 4.89 94 91 93

Almost all communities have a high degree of land ownership (Table 64). The average

size of landholdings is fairly large compared to the rest of the state or India in general, because of

plantation-based agriculture in Wayana d. However, the plantation economy does not appear to

ensure high levels of income for all households. The findings on per capita annual income

across the communities show that it ranges between about Rs. 10,000 (Hindus) to Rs. 12,000 for

Muslims and Rs. 13,000 for Christians. There are high levels of incidence of indebtedness

ranging from 51% for Hindus, 60% for Muslims to 85% for Christians. There is a positive

correlation between levels of income, incidence of indebtedness and intensity of debt as well. A

redeeming feature is that dependence on informal sources for credit appears to be almost

negligible (3%), with most of the indebtedness being from formal institutional sources.

Table 64: Access to Assets and Amenities of Households Surveyed in Wayanad (%) Community With Land Housing Electricity Public In-House Semi Pucca Pucca Drinking Toilet Water Supply

73

Hindu 92 67 13 71 76 28 Muslim 97 68 21 87 72 35 Christian 95 60 31 82 80 48 All 95 66 21 80 78 36

Universal public distribution system (PDS) is an important feature of the Kerala

economy, and in Wayanad, more than 80% report accessing the same. But, about one-fourth of

the respondents did complain about insufficient quantity, poor quality or non-availability on

time.

The major problem s identified by the survey are especially regarding STs who live in

remote and forest areas, and who are marginalized in accessing benefits of plan programmes.

Though education and health facilities are well provided, remote areas and tribal populations do

face problems in accessing education at high school and at higher levels, and medical facilities for

serious ailments. Most of the work available is of a casual nature. The responses of the

households show that their concerns are for better (high school and above) education and

employment (for more days and regular).

7.5 Andaman and Nicobar Islands

Nicobar of Andaman and Nicobar Islands is one of the remotest districts of the Indian

Union. Interestingly, Nicobar is identified as an MCD in the B2 category i.e. on the basis of

deficits in amenities rather than on socio -economic indicators. The survey was conducted in the

post-Tsunami reconstruction phase, after the devastation that wiped out a substantial number of

settlements along the Nicobar, and with the major source of livelihood based on seafaring. The

survey was to be carried out in the islands of Car Nicobar, Mancowry group of islands and in

Great Nicobar, but the survey was restricted to Car Nicobar and Great Nicobar because of the

logistic problems posed by the post-Tsunami reconstruction and the advancing monsoon.

Added to that is the fact that the presentation refers to the population merely in two groups:

Christians and non-Christians.

74

The majority of Nicobarese are Christians but of tribal origin, and the district has a traditional form of governance called the Tribal Council represented by headmen of villages.

The Council works in close coordination with the district administration of the government.

The literacy levels are relatively high for both Christians (males 82%, females 77%) and non-

Christians (males 91%, females 80%). School enrolments are as high as 98% to 99% for both the communities; and the level of retention is high up to secondary level. Government or aided schools cater to 96% of Christians and 87% of non-Christians. The location of school facilities are within one kilometre for 83% of non-Christians while most of the Christians have to go more than one kilometre. Parental aspirations for higher education for children are high among both the groups, but access to such facilities is limited. Health facilities are mostly provided by the government: 99% of Christians and 92% of non-Christians access government health facilities. The annual private family expenditure on health for non-Christians is over Rs. 42000, almost ten times higher than it is for Christians (Rs. 4900), but this difference is not explained.

Institutional deliveries (child birth) are high for both Christians (90%) and non-Christians (73%).

Immunization is at a high level for both the communities and is entirely government provided.

Though the method of estimation of work participation and occupational distribution in the report leaves much to be desired *, female work participation is very low and salaried government or private employment is the main source of employment for both Christians and non-Christians. Agriculture is the second important source of work for Christians, whereas it is casual labour for non-Christians. Amenities as recorded in the survey may not reflect the usual situation, because it was in the context of post-Tsunami reconstruction. However, in spite of this context, what is surprising is that 94% of Christian households and 96% of non-Christian households had electricity connections – a feat which eludes most of the mainland MCDs.

Similar is the situation relating to toilets. 91% of Christians and 94% non-Christians had in-

* This is a common problem for most of the reports prepared by the institute which prepared the present one too. 75 house toilets. Drinking water and proper housing are, however, are in a bad condition, largely because of the Tsunami, and reconstruction was going on at the time of survey.

VIII

Concluding Remarks

If there is one word to capture the results of the MCD reports, it is ‘diversity’.

Paradoxically, the first reaction of anyone who knows India is that diversity is nothing new.

However, in the context of policy interventions specific to MCDs, paying special attention to not only inter-religious but also intra-religious, inter-regional as well as intra-regional differences becomes a pre-condition. To the extent the MCD reports unfold these diversities, the basic purpose is served. However, the inherent limitation of the MCD reports is that they do not look beyond the district, in the sense of spatial or historical linkages. Conscious efforts to identify the spatial linkages of the local with the state, region and nation in an economic and administrative sense, and historical linkages in terms of the processes of evolving inter-and -intra community relations along with the rich data on the specific conditions in the respective MCDs, would help better interventions. For instance, there is a fascinating account of the process of emergence of the Muslim community and the social composition of the Indian Muslims across regions

(Saberwal, 2010). It invokes a general model of gradual change in religious identities by premising it on the ‘Hindu method of tribal absorption’ as witnessed in the case of Juang from

Central Orissa, and Oraon and Munda in the region presently part of Jharkhand. The framework helps to und erstand regional diversity in the social composition of Muslims across the country, the Buddhists in North-East States, the neo -Buddhists in Maharashtra and the

Christians in the North East. Similar are the insights on the nature of educational deprivation among certain minorities, either Buddhists in some parts of North East or Muslims at large.

There is a strong view emerging that reduction of the educational gap among certain minority groups needs to be addressed by taking into consideration all the dimensions like ‘access’ by

76 increasing educational facilities, improving ‘attributes’ like special efforts like scholarships and improving ‘opportunities’ by addressing discrimination in the labour market (Desai and Kulkarni,

2010). In summing up, attention is paid to a large minority with concentration in the Northern and Eastern State, which helps in discerning certain patterns.

There is a wide recognition of the comparatively higher educational backwardness of the

Muslim community in many parts of the co untry. The SCR discussing the representations received, observed: “Most representations deal with equity and security related issues.

Interestingly, the topic of education was raised most frequently in the representations, followed by reservation, employment and security related issues. … it certainly reflects that education is one of the most serious concerns for the Muslim community in India” (SCR, p. II). However, in

10 out of 21 States, Muslims do better in education than the average levels (Wilkinson, 2007). It is argued that interventions should be state/region-specific. For instance, even in UP, the education/literacy attainments of Muslims in Rampur, Bijnore, and Siddharthnagar are almost on par with Hindus. In West Bengal, the literacy performance of Muslims in Haora and Dakshin

Dinajpur is much better than that of the Hindus; and in Assam, Muslim literacy is better than the

Hindu literacy. The basic question is: can the respective states design interventions based on the region-specific experiences to bridge the gap in the differences in educational levels?

The above analysis shows that as far as Assam is concerned, by and large, the intra- community differences in socio-economic factors like education, access to land etc. are much less than inter-district variations. Also the deficits in socio -economic factors are not as severe as in the case of Bihar or U.P. But, in the case of amenities, the deficits particularly in housing and electricity connectivity are high. These are also the amenities where it is not so much regional variation as intra-community variation that is strikingly high.

While backwardness is general to all communities in MCDs in the four major states focused here, there are certain specific disabling conditions associated with Muslims. The reports help in drawing a broad picture of disabling conditions under which the Muslims live.

77

Though predominantly living in rural and semi-urban areas, Muslims suffer from high levels of deprivation in terms of landlessness, high levels of dependency partly due to restriction on women working outside the household, mostly depending on self -employment with low skills and low productive work, high degree of entirely male migration in search of livelihood, poor formal education, low credit rating, high caste-community discrimination, and low access to institutional credit.

Dependence on crafts and certain traditional artisanal activities is much higher among

Muslims. Restrictions on women’s physical work outside home, combined with certain cultural constraints keep female work participation at a very low level. Muslim women’s work participation is mostly in the form of self-employment and largely in home-based work, as a part of the putting -out system characterized by low productivity and very low wages. Muslim men are mostly dependent on non-agricultural informal skills. Most of the informal crafts and skills are still caste/religion-based, but often these communities have very poor credit rating.

‘Informal Capital’ is also caste/religion-based, like the Marwari credit. Informal credit is often extended to the likes of the merchant/trader community rather than the real artisan/craftswoman producer. The caste-culture of informal credit constrains the craftsman or skilled producer to emerge as producer-entrepreneur. Most of the Muslims in the informal sector are caught in the web of relations that make skills/crafts subordinate to merchant capital.

The need is to build institutions that help the artisans not only sharpen their skills and improve productivity, but also enable them to organize production and be able to improve bargaining power to participate in and compete in the larger market. Interventions to improve access to formal credit on priority and organized institutional help ni establishing market linkages become essential for the Muslim community.

In terms of growth and development, the two critical questions are: Does growth and development lead to improvement in educational status and access to basic amenities? Does relatively better ‘development’ (per capita GSDP) reflect in reduced gaps in educational and

78

access to amenities? To answer these questions some of the findings on the state of literacy,

access to amenities like pucca housing, drinking water, electricity and WC toilet facilities are

pooled together and presented in Tables 65 to 69. With the exception of pucca housing and

potable water, the definitions of which have been the source of some inconsistency and

controversy, the other indicators do reflect certain positive association with ‘development’. As

pointed out earlier (see Table 1), in terms of both growth performance and per capita GSDP,

West Bengal and Assam are at a much higher level compared to U.P. and Bihar. This is reflected

in the levels of literacy (Table 65), household access to electricity (Table 68) and in-house W.C.

toilet facility (Table 69).

But, if the question is whether higher growth and ‘development’ have reduced inter-

community differences, the answer seems to be in the negative. Though with growth and

development the levels of literacy, electricity and in-house sanitary facilities have improved, the

inter-community differences too remained but at a higher level! However, it must be said that

Assam stands on a different footing, with inter-community differences in most of the indicators

remaining at a relatively low-level.

Table 65: Comparative State of Literacy Among Religious Communities Across the Four States (%)

Religious U.P. Bihar West Bengal Assam Community Hindu-General[M12]* 58* 79 70.6 85 Hindu-OBC - 60 62.5 81 Hindu-SC/ST - 49 65.0 78 Muslim -General* 48* 59 53.4 72 Muslim -OBC - 54 - - *Refers to overall Hindus and Muslims respectively

Table 66: Comparative State of Pucca Housing Across the Religious Communities in the Four States (%)

Religious U.P. Bihar West Bengal Community Assam* Hindu-General 49 21 26.3 14.8 Hindu-OBC 36 12 15.9 8.9 Hindu-SC/ST 33 12 7.0 7.3 Muslim -General 38 8 9.9 5.0 Muslim -OBC 30 6 - - *There are problems of comparable data from Assam.

79

Table 67: Comparative Household Access to Potable Drinking Water Across Religious Communities in the Four States (%)

Religious U.P. Bihar West Bengal Assam* Community Hindu-General 80 67 50.3 59 Hindu-OBC 78 61 52.0 48 Hindu-SC/ST 63 40 37.9 47 Muslim -General 75 67 37.8 59 Muslim -OBC 62 65 - -

Table 68: Comparative State of Households with Electricity Among Religious Communities in the Four States (%)

Religious U.P. Bihar West Bengal Assam* Community Hindu-General 36 22 60 39 Hindu-OBC 25 12 45 28 Hindu-SC/ST 19 7 26 25 Muslim -General 22 10 30 15 Muslim -OBC 21 8 - -

Table 69: Comparative State of Households with W.C. Toilet Facility Among Religious Communities in the Four States (%)

Religious U.P. Bihar West Bengal Assam* Community Hindu-General 30 23 65 51 Hindu-OBC 21 8 51 53 Hindu-SC/ST 17 2 35 54 Muslim -General 36 12 34 47 Muslim -OBC 30 5 - -

Interestingly, of the three critical dimensions – equity, security and identity – identified

by the ‘mother report’ (SCR) on the Muslim minority, the domain of the MCD survey reports

are not so much on security and identity but substantially on equity, not merely because of the

fact that data related to aspects of security and identity are difficult to obtain but essentially

because the MCD surveys are aimed at information that enables prompt and better intervention.

Further, the state has a constitutional obligation to ensure equity which can be translated into

operational interventions, and the surveys are expected to help in that direction. While security

and identity are the issues that remain, the neglect over the years and urgency to correct this

neglect naturally needs a focus on equity. With all the limitations, the overview brings together

data disaggregated to the district level on caste, tribe and community/religion basis. To that

extent, it could be seen as a humble contribution in discerning district level differences that

would be of help in designing interventions by appropriate state level agencies.

80

This overview is truncated. The analysis largely confined to fifty two Muslim minority concentration districts and the four states in which these districts are concentrated, for the reasons mentioned earlier. What is the outcome of this overview? It helps raise policy relevant questions for some of which clear answers have to be sought. It identifies a number of complex social and administrative puzzles for which no clear solutions exist. By raising these questions and drawing attention to the puzzles, it goes a step beyond individual MCD survey reports. The overview attempts to identify patterns, similarities or differences among the districts by treating the survey reports as a set at the state level. It highlights intra-community, inter-community as well as inter-regional variations. There are questions like why does a state sponsored programme like PDS or IAY show wide regional or inter-community variations within a state? Historical and cultural aspects apart, could there be agency problems that could be discerned and addressed? It also helps to see that there is nothing like ‘single’ multi-sector planning for all the districts, but a need to look for nuanced and situation-specific interventions to reduce development deficits. The extremes in situations and deviations in outcomes may also help raise questions as to whether it is necessary to temper the interventions by translating the ‘weak equity axiom’ by devoting more attention and resources to the most weak and needy, or whether there is any room for considering, in the neoliberal way, that all that js spent on the weak and the poor would go down the drain – leaving market intervention or at the most cash transfers as the solution?!

Some of the important areas for intervention arising out of the above analysis relate to education and skill development, infrastructure including improved supply of electricity, increased access to institutional credit and improved housing conditions. Irrespective of the

‘development deficit’ , the highest priority is to be given to improving educational facilities that ensure completion of at least secondary education. Some basic school infrastructure improvements like the location of the school within easy reach, separate schools for girls,

81 provision of toilet facilities in schools, vernacular / Urdu medium as medium of instruction at least in the primary classes could make considerable difference for minority girls’ education.

Annexure A

Some Aspects of Minority Concentration Districts (90)

Minorities: Muslims (13.4%), Sikhs (1.9%), Christians (2.3%), Buddhists (0.8%), & Zoroastrians (0.007%) (NCMA 1992).

Minority Concentration : Distric ts with at least 25% of minority population excluding Districts those which have better socio-economic indicators higher than the national average (Rural)

Socio-Economic and Amenities Parameters:

I. Socio -Economic

i. Literacy Rate ii. Female Literacy Rate iii. Work Participation Rate iv. Female Work Participation Rate

II. Basic Amenities

i. Houses with Pucca Walls(%) ii. Households with Safe Drinking Water (%) iii. Households with Electricity (%) iv. Households with W/C Latrines (%)

Category ‘A’: Districts with values below national average for both (I & II) sets of parameters: More Backward=53.

Category ‘B’: Districts with values below national average for either of the two (I or II) parameters: Backward=37.

82

Annexure B Category-wise Distribution of Minority Concentration Districts (MCDs) Across States and Union Territories

State / Union Minority Concentration Districts Territory A B1 B2 All 1. Arunachal Pradesh (4) (3) - (7) 1. East Kameng 1. Tawang 2. Lower Sabhansri 2. West Kameng 3. Changlang 3. Paum Pare 4. Tirap 2. Assam (12) - (1) (13) 1. Kokrajhar 1. North Cachar Hills 2. Bhubri 3. Gopalpara 4. Bongaigaon 5. Barpeta 6. Darrang 7. Marigaon 8. Nagaon 9. Cachar 10. Karimganj 11. Hailakandi 12. Karnarup 3. Bihar (7) - - (7) 1. Araria 2. Kishangunj 3. Purniya 4. Katihar 5. Sitamari 6. Pas. Champaran 7. Darbhanga

4. Jharkhand (2) - (2) (4) 1. Sahibganj 1. Ranchi 2. Pakur 2. Gulma

5. Manipur (1) - (5) (6) 1. Thonbal 1. Senapati 2. Tamarglong 3. Churachandpur 4. Ukhrul 5. Chandel

6. Meghalaya (1) - - (1) 1. West Garo Hills

7. Orissa (1) - - (1) 1. Gajapati

83

State / Union Minority Concentration Districts Territory A B1 B2 All 8. Uttar Pradesh (15) (6) - (21) 1. Bulandshahar 1. Lucknow 2. 2. Saharanpur 3. Barabanki 3. 4. Kheri 4. 5. Shahjahanpur 5. Baghpat 6. Moradabad 6. 7. Rampur 8. Jyotiba Phule Nagar 9. Bareily 10. Pilibhit 11. Bahraich 12. Shrawasti 13. Balrampur 14. Siddharthanagar 15. Bijnor 9. Uttaranchal - (2) - (2) 1. Udham Singh Nagar 2. Haridwar 10. Haryana - (2) - (2) 1. Gurgaon 2. Sirsa 11. West Bengal (9) (3) - (12) 1. Uttar Dinajpur 1. Haora 2. Dakshin Dinajpur 2. North 24 Parganas 3. Maldah 3. Kolkata 4. Murshidabad 5. Bibhumu 6. Nadia 7. 8. Barddhman 9. Koch Bihar 12. Delhi - (1) - (1) 1. North 13. Karnataka - (2) - (2) 1. Gulbarga 2. Bidar 14. Madhya Pradesh - (1) - (1) 1. Bhopal 15. Jammu & Kashmir - - (1) (1) 1. Leh (Ladakh) 16. Kerala - - (1) (1) 1. Wayanad 17. Maharashtra (1) - (3) (4) 1. Parbhani 1. Bulanda 2. Washim 3. Hingoli 18. Mizoram - - (2) (2) 1. Lawngtlai 2. Mamit 19. Sikkim - - (1) (1) 1. North Sikkim 20. Andamans - - (1) (1) 1. Nicobar A: Districts which have ‘deficits’ in both Socio-economic indicators and basic amenities. B1: Districts with ‘deficits’ in socio-economic indicators. B2: Districts with ‘deficits’ in basic amenities.

84

Annexure 1: Religion and Caste-wise Sex Ratio in MCDs of U.P. District Hindu Muslim SC/ST General OBC Total General OBC Total Siddharthnagar 824 813 818 819 892 895 892 Badaun 774 812 791 786 734 774 764 Bahraich 855 809 784 807 854 908 880 Lakhimpur 867 829 862 858 784 888 844 Muzaffar Nagar 870 673 847 845 789 900 878 Balrampur 772 834 800 798 938 888 897 Pilibhit 913 858 893 897 888 736 775 J.P. Nagar 792 976 726 774 557 761 734 Moradabad 776 896 747 775 884 901 892 Saharanpur 896 762 784 824 1000 810 810 Barabanki 832 766 834 826 957 900 906 Bijnore 809 833 923 842 956 888 891 Baghpat 772 775 713 741 1667 866 880 Shravasti 857 987 936 923 929 991 988 Lucknow 937 873 793 886 1250 925 930 Bareilly 761 883 741 759 933 833 864 Rampur 767 1111 690 739 600 789 783 Bulandshahar 820 786 802 804 955 785 828 Shahjahanpur 766 864 826 809 697 861 832 Average* 829 830 804 817 841 860 855 *Average for the 21 MCDs in UP.

Annexure 2: District-wise Dropouts Among 5 to 15 Age Group (%) District Hindu Muslim SC/ST General OBC Total General OBC Total

Siddharthnagar 0.65 0.00 0.58 0.50 2.02 0.68 1.21 Badaun 4.33 2.11 2.79 3.45 3.79 6.73 6.00 Bahraich 6.42 2.45 2.80 3.75 1.73 8.06 5.98 Lakhimpur 7.47 3.40 5.51 5.90 3.64 8.43 6.49 Muzaffar Nagar 5.03 3.39 3.66 4.48 9.52 9.09 8.48 Balrampur 3.26 1.55 1.28 1.96 1.05 2.13 1.94 Pilibhit 5.02 0.00 3.25 3.58 9.47 9.00 8.66 J.P. Nagar 1.10 1.41 0.78 0.99 1.69 4.43 4.81 Moradabad 1.96 0.00 1.68 1.59 4.24 1.58 2.39 Saharanpur 1.41 0.51 1.32 1.21 0.00 6.42 5.39 Barabanki 8.60 1.22 3.02 5.28 3.85 7.26 6.89 Bijnore 2.86 1.15 0.42 2.00 0.00 3.43 3.25 Baghpat 3.05 0.80 1.62 1.96 0.00 3.80 3.72 Shravasti 11.30 4.17 5.98 7.12 10.53 15.61 15.20 Lucknow 4.87 3.31 1.11 3.68 0.00 7.69 7.39 Bareilly 5.17 14.43 6.04 6.47 4.05 5.88 5.67 Rampur 0.00 0.00 0.48 0.26 0.00 2.00 1.92 Bulandshahar 0.78 0.42 1.35 0.94 6.49 2.72 3.56 Shahjahanpur 4.87 2.68 5.22 4.73 4.76 5.33 5.32 Average 4.01 2.20 2.86 3.23 3.88 5.57 5.25

85

Annexure 3: District-wise Never Enrolled (5-15 Age Group)(%) District Hindu Muslim SC/ST General OBC Total General OBC Total Siddharthnagar 10.78 4.21 7.02 7.63 5.72 7.48 6.70 Badaun 15.05 16.20 20.89 17.34 25.59 40.65 35.55 Bahraich 12.16 4.91 8.57 9.01 12.14 14.17 13.46 Lakhimpur 11.52 4.68 4.72 7.43 12.73 14.46 14.23 Muzaffar Nagar 4.64 0.00 0.73 3.06 2.38 6.68 6.10 Balrampur 20.52 3.61 10.90 12.49 13.68 19.34 18.31 Pilibhit 8.36 5.00 4.33 5.57 24.21 19.91 20.90 J.P. Nagar 8.52 5.63 7.62 7.97 8.47 6.12 6.48 Moradabad 8.96 8.11 7.14 7.94 16.10 3.60 6.15 Saharanpur 6.84 3.57 3.69 5.13 0.00 8.26 10.05 Barabanki 7.26 2.44 8.29 7.28 30.77 11.20 13.04 Bijnore 3.05 3.45 0.00 2.24 6.06 2.96 3.11 Baghpat 3.82 1.60 4.18 3.67 0.00 5.71 5.59 Shravasti 8.22 1.19 11.02 8.77 13.16 20.89 20.27 Lucknow 2.83 0.55 3.33 2.57 0.00 4.45 4.28 Bareilly 8.91 9.28 15.36 12.95 8.11 9.56 8.51 Rampur 0.63 0.00 0.00 0.26 0.00 0.15 0.15 Bulandshahar 0.78 4.22 2.26 2.16 0.00 2.72 2.08 Shahjahanpur 14.33 14.77 11.61 13.00 31.75 35.53 35.11 Average 7.97 5.06 7.56 7.39 13.58 11.78 12.12

Annexure 4: Tertiary Sector Employment – U.P. (%) District Hindu Muslim SC/ST General OBC Total General OBC Total Siddharthnagar 8.5 26.5 10.4 12.9 19.7 14.8 16.9 Badaun 3.1 3.8 2.4 3.0 5.3 4.1 4.3 Bahraich 7.5 20.8 10.2 11.0 14.6 17.3 16.4 Lakhimpur 7.5 9.1 10.0 8.8 14.3 17.3 15.9 Muzaffar Nagar 7.8 15.7 12.4 9.8 4.9 12.7 11.2 Balrampur 8.1 25.3 8.0 11.3 30.6 19.1 20.4 Pilibhit 3.4 16.0 7.4 6.8 14.9 5.6 8.5 J.P. Nagar 3.6 17.9 2.9 4.2 37.5 13.1 15.4 Moradabad 6.8 11.0 5.8 6.8 5.2 6.5 6.1 Saharanpur 47.9 29.4 33.4 38.4 61.9 63.3 Barabanki 7.7 20.4 8.7 9.5 19.3 10.6 11.7 Bijnore 5.7 21.7 8.8 8.4 11.8 9.8 9.9 Baghpat 17.9 27.6 16.6 19.0 60.0 12.2 13.6 Shravasti 8.6 16.5 10.3 10.7 2.8 15.0 14.4 Lucknow 14.9 31.0 21.3 19.4 50.0 39.9 39.6 Bareilly 9.9 11.2 10.9 10.6 15.5 14.8 15.1 Rampur 2.9 6.9 1.5 2.3 0.0 8.8 8.7 Bulandshahar 6.1 13.4 7.9 8.7 0.8 6.8 5.3 Shahjahanpur 5.1 8.8 5.2 5.6 13.6 5.5 6.6 Average 9.5 18.7 9.9 11.0 14.0 14.0 14.2

86

Annexure 5: District-Wise Average Family Size – U.P District Hindu Muslim Share % SC/ST General OBC Total General OBC Total of Muslim Population Siddharthnagar 6.9 6.9 7.0 7.0 7.9 7.7 7.8 Badaun 5.4 5.4 5.7 5.5 6.6 6.2 6.3 Bahraich 6.0 7.4 6.2 6.3 7.5 7.0 7.2 34.8 Lakhimpur 6.9 7.1 7.4 7.1 7.1 6.8 6.9 Muzaffar Nagar 5.8 5.1 5.6 5.7 6.3 6.1 6.1 38.1 Balrampur 6.4 7.2 6.8 6.7 9.5 7.7 7.9 36.7 Pilibhit 5.4 6.2 6.1 5.9 6.8 6.6 6.6 J.P. Nagar 6.0 5.8 6.0 5.9 6.8 6.5 6.5 39.4 Moradabad 5.3 5.6 5.5 5.5 6.5 6.2 6.3 45.5 Saharanpur 5.5 6.1 5.4 5.6 4.0 6.5 6.6 39.1 Barabanki 4.7 5.2 5.3 5.1 6.4 5.9 6.0 Bijnore 5.6 4.9 5.4 5.4 5.9 6.2 6.2 41.7 Baghpat 5.4 5.2 5.2 5.3 5.3 6.3 6.2 Shravasti 5.5 6.1 6.1 5.9 6.0 6.3 6.3 Lucknow 5.4 5.6 5.4 5.4 4.5 6.0 6.0 Bareilly 5.6 5.7 5.8 5.7 6.5 6.3 6.4 33.9 Rampur 6.1 8.1 5.9 6.1 6.0 6.7 6.7 49.1 Bulandshahar 6.6 6.3 6.5 6.5 8.1 6.9 7.2 Shahjahanpur 5.1 5.5 5.4 5.3 6.2 6.1 6.1 Average 5.7 6.1 5.9 5.9 7.1 6.5 6.6

Annexure 6: District-wise Dependency Ratio – U.P District Hindu Muslim SC/ST General OBC Total General OBC Total

Siddharthnagar 91.3 84.0 100.8 94.5 104.6 101.8 102.9 Badaun 98.2 98.4 92.5 96.2 95.3 98.0 97.3 Bahraich 91.8 81.4 90.9 89.5 96.4 114.6 106.3 Lakhimpur 101.2 94.4 90.9 95.7 99.7 109.4 105.6 Muzaffar Nagar 85.9 75.5 76.6 82.0 109.2 103.4 105.1 Balrampur 81.2 64.4 83.0 78.2 80.4 85.9 85.3 Pilibhit 90.0 90.6 79.0 83.0 100.0 91.0 94.6 J.P. Nagar 78.4 72.3 72.2 75.3 81.0 80.6 80.2 Moradabad 86.4 61.4 81.5 80.4 94.0 86.5 87.4 Saharanpur 70.6 63.3 65.5 67.1 100.0 100.0 105.4 Barabanki 91.5 70.3 83.4 85.1 62.2 98.1 94.0 Bijnore 92.3 72.4 77.8 85.7 114.6 107.0 107.1 Baghpat 77.2 60.4 67.3 68.8 100.0 89.8 88.7 Shravasti 104.3 94.8 97.7 98.9 151.2 119.6 121.2 Lucknow 99.1 70.1 93.4 91.8 350.0 90.3 92.1 Bareilly 72.0 54.3 71.5 70.0 71.2 80.0 78.6 Rampur 64.4 86.9 63.0 64.6 50.0 72.5 72.7 Bulandshahar 75.8 64.5 71.1 70.9 90.7 82.8 84.4 Shahjahanpur 100.3 83.8 93.8 94.5 88.2 117.0 110.9 Average 86.8 74.2 81.4 82.3 94.3 94.6 94.6

87

Annexure 7: Indebtedness (%HH) in U.P. MCDs District Hindu Muslim SC/ST General OBC Total General OBC Total

Siddharthnagar 35.5 29.2 30.5 31.8 33.8 27.0 29.5 Badaun 15.4 12.4 8.8 12.7 13.0 34.0 26.3 Bahraich 44.1 35.6 30.5 35.2 28.8 44.3 39.2 Lakhimpur 47.2 42.6 45.8 45.8 44.7 47.2 45.9 Muzaffar Nagar 29.8 16.3 22.9 26.4 16.3 20.4 19.8 Balrampur 7.9 7.2 9.1 8.3 16.7 8.1 9.3 Pilibhit 63.4 61.1 63.9 63.6 46.0 44.2 45.8 J.P. Nagar 65.2 38.1 64.6 63.1 60.7 57.2 57.3 Moradabad 58.8 58.3 47.8 53.2 66.7 28.7 36.7 Saharanpur 41.3 33.6 31.5 36.0 0.0 42.0 41.9 Barabanki 29.2 39.1 35.8 33.2 14.3 17.9 17.5 Bijnore 10.9 6.2 5.4 8.7 0.0 6.7 6.4 Baghpat 32.4 23.7 31.2 30.2 33.3 46.1 46.0 Shravasti 43.2 38.8 36.6 38.8 38.9 51.1 50.2 Lucknow 20.7 20.2 17.3 19.7 0.0 24.1 23.1 Bareilly 26.9 29.6 34.7 31.9 39.7 42.4 38.9 Rampur 30.2 35.7 21.2 25.6 25.0 21.3 20.7 Bulandshahar 55.5 49.7 51.7 52.4 47.9 53.9 52.0 Shahjahanpur 29.0 41.3 30.3 31.4 11.1 22.6 21.1 Average 35.4 32.1 34.9 34.7 33.3 31.0 31.3

Annexure 8: Institutional Sources (%) – U.P. District Hindu Muslim SC/ST General OBC Total General OBC Total

Siddharthnagar 33.33 47.06 34.02 36.08 31.03 6.15 17.46 Badaun 46.67 53.85 72.22 53.95 33.33 28.38 30.77 Bahraich 34.88 70.97 23.93 34.19 35.71 11.63 17.39 Lakhimpur 48.89 72.73 55.36 55.63 28.85 20.93 23.91 Muzaffar Nagar 28.85 50.00 20.83 27.50 28.57 6.94 9.52 Balrampur 46.67 70.00 44.00 50.00 100.00 62.50 70.97 Pilibhit 27.78 39.29 44.97 38.78 19.35 15.00 15.97 J.P. Nagar 35.71 50.00 45.51 40.59 31.58 33.33 33.33 Moradabad 35.54 58.33 48.55 44.19 33.33 37.18 35.71 Saharanpur 14.52 25.00 20.22 18.39 0.00 13.43 16.05 Barabanki 70.73 80.00 75.00 73.91 25.00 46.00 44.44 Bijnore 30.56 25.00 75.00 37.50 0.00 21.74 21.74 Baghpat 9.84 60.71 49.07 38.58 0.00 8.18 7.89 Shravasti 22.09 50.00 27.27 29.08 71.43 10.45 13.29 Lucknow 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Bareilly 38.46 29.41 43.70 41.18 17.39 13.58 15.45 Rampur 85.19 100.00 65.22 77.14 0.00 66.67 65.79 Bulandshahar 21.97 26.09 21.21 22.62 22.22 17.24 18.42 Shahjahanpur 52.00 79.49 62.11 61.72 75.00 23.81 31.25 Average 33.65 49.03 41.66 39.33 31.18 21.71 23.75

88

Annexure 9: District-wise In-House Drinking Water– U.P. (%) District Hindu Muslim SC/ST General OBC Total General OBC Total Siddharthnagar 67.47 85.85 86.38 80.58 86.15 83.64 84.48 Badaun 63.86 93.26 87.11 76.41 87.04 64.59 73.11 Bahraich 50.28 73.56 62.25 60.39 72.50 68.75 69.62 Lakhimpur 59.20 77.78 80.44 70.84 85.29 72.67 77.36 Muzaffar Nagar 55.45 89.80 72.29 63.95 81.40 66.33 68.16 Balrampur 64.92 95.50 78.41 77.21 80.56 85.08 84.13 Pilibhit 76.85 88.89 84.88 82.35 75.56 83.18 81.48 J.P. Nagar 90.48 100.00 91.79 91.68 89.29 97.38 96.56 Moradabad 82.35 94.44 92.26 88.81 88.33 89.41 89.58 Saharanpur 82.89 77.86 88.89 84.18 100.00 75.64 72.63 Barabanki 45.32 62.50 59.41 53.49 71.43 63.43 64.31 Bijnore 44.41 89.23 71.81 57.69 33.33 57.14 56.23 Baghpat 55.08 73.50 70.38 66.51 100.00 50.87 52.72 Shravasti 62.84 91.84 78.23 75.96 77.78 81.70 81.18 Lucknow 34.52 31.78 20.92 30.47 NA 30.00 29.45 Bareilly 79.46 77.78 85.22 82.85 87.93 84.18 86.42 Rampur 88.76 100.00 95.85 92.91 100.00 95.36 95.56 Bulandshahar 73.06 86.05 79.19 78.96 72.92 83.55 80.69 Shahjahanpur 56.47 75.90 76.22 68.55 85.71 77.96 78.41 Average 63.42 79.77 77.73 72.25 81.75 74.85 76.07

Annexure 10: District-wise Pucca House – U.P. (%) District Hindu Muslim SC/ST General OBC Total General OBC Total Siddharthnagar 46.39 59.43 48.03 49.73 60.77 48.13 53.45 Badaun 21.75 39.33 25.77 25.88 29.63 23.44 25.38 Bahraich 28.25 45.98 17.29 24.55 21.25 14.20 16.15 Lakhimpur 32.40 45.37 35.56 36.02 13.73 21.12 18.49 Muzaffar Nagar 47.44 77.55 46.99 50.09 72.09 36.39 39.66 Balrampur 20.42 54.95 23.48 28.62 58.33 27.46 30.84 Pilibhit 46.76 38.89 35.28 39.43 26.67 30.84 30.86 J.P. Nagar 38.10 54.76 48.88 43.84 32.14 39.30 38.17 Moradabad 33.94 61.11 38.38 39.49 25.00 35.59 32.57 Saharanpur 35.23 43.57 35.56 37.01 100.00 40.38 38.95 Barabanki 30.71 37.50 39.85 35.55 42.86 27.61 28.96 Bijnore 28.43 49.23 42.28 34.91 40.00 24.01 24.93 Baghpat 26.74 56.41 48.68 43.72 33.33 16.52 17.15 Shravasti 20.22 37.76 30.11 28.48 38.89 21.28 22.75 Lucknow 15.75 14.06 15.38 15.36 NA 19.29 18.49 Bareilly 29.73 38.89 25.07 27.67 18.97 25.99 22.26 Rampur 41.34 78.57 37.33 40.49 NA 34.87 34.25 Bulandshahar 70.00 77.46 74.00 73.59 72.92 62.99 65.69 Shahjahanpur 15.95 34.94 24.39 22.59 42.86 18.82 22.47 Average 32.54 48.90 36.26 36.57 37.68 29.83 30.95

89

Annexure 11: District-wise In-House Toilet Facilities– U.P. (%) District Hindu Muslim SC/ST General OBC Total General OBC Total Siddharthnagar 6.02 12.26 1.79 5.08 13.85 8.41 10.63 Badaun 9.47 44.94 18.56 18.13 37.96 19.62 26.89 Bahraich 6.78 16.09 6.63 8.02 15.00 3.98 7.31 Lakhimpur 6.80 12.96 11.11 9.61 23.53 11.80 16.23 Muzaffar Niger 25.64 44.90 42.77 32.83 74.42 52.72 54.19 Balrampur 5.76 30.63 4.92 10.25 33.33 7.80 10.48 Pilibhit 11.57 33.33 17.24 16.22 44.44 20.56 27.16 J.P. Nagar 16.83 19.05 14.18 15.84 50.00 44.98 45.04 Moradabad 14.93 38.89 30.98 25.93 35.00 52.54 47.56 Saharanpur 37.92 52.86 50.00 45.48 100.00 53.85 50.00 Barabanki 5.24 20.31 7.01 7.64 46.43 15.30 18.18 Bijnore 12.14 44.62 28.19 20.68 66.67 46.81 47.54 Baghpat 26.74 54.70 43.70 40.78 33.33 18.70 18.41 Shravasti 6.56 16.33 5.91 7.66 11.11 3.40 3.92 Lucknow 14.32 12.40 12.24 13.44 NA 4.29 4.11 Bareilly 25.95 31.48 20.05 22.82 56.90 43.50 49.06 Rampur 62.57 71.43 66.36 64.88 75.00 71.18 71.27 Bulandshahar 17.89 22.09 21.67 20.58 35.42 28.48 30.35 Shahjahanpur 11.21 26.51 15.68 15.45 80.00 16.67 25.99 Average 16.91 29.58 20.95 20.55 35.78 30.10 31.16

Annexure 12: District-wise Electricity – U.P. (%) District Hindu Muslim SC/ST General OBC Total General OBC Total Siddharthnagar 11.4 44.3 17.6 20.9 27.7 20.6 23.9 Badaun 9.5 21.3 10.8 11.8 24.1 7.2 13.0 Bahraich 5.6 21.8 5.8 8.0 11.3 4.0 6.2 Lakhimpur 5.6 17.6 12.0 10.3 14.7 6.8 9.8 Muzaffar Nagar 24.0 67.3 40.4 33.2 20.9 25.9 24.9 Balrampur 7.9 37.8 17.8 18.4 50.0 22.4 25.4 Pilibhit 7.9 16.7 17.8 14.3 17.8 9.3 13.0 J.P. Nagar 6.7 7.1 7.5 7.0 7.1 10.9 10.3 Moradabad 10.0 34.7 24.9 20.5 10.0 29.2 24.8 Saharanpur 72.8 60.7 78.1 72.5 100.0 64.1 63.2 Barabanki 8.2 35.9 22.9 17.8 35.7 17.5 19.2 Bijnore 19.8 46.2 38.9 28.5 33.3 24.6 25.2 Baghpat 46.5 76.1 72.4 65.6 100.0 27.8 29.3 Shravasti 4.9 14.3 8.9 8.6 11.1 6.0 6.3 Lucknow 18.6 18.0 26.0 20.4 50.0 12.1 12.2 Bareilly 10.3 25.9 11.1 12.1 19.0 13.6 14.7 Rampur 46.4 50.0 38.7 42.4 NA 40.3 40.6 Bulandshahar 30.0 38.2 29.7 31.9 20.8 17.5 18.6 Shahjahanpur 8.6 25.3 14.6 13.8 42.9 14.5 18.5 Average 19.1 35.8 25.2 24.3 22.2 20.8 21.3

90

Annexure 13: Access to PDS (%) – U.P. District Hindu Muslim SC/ST General OBC Total General OBC Total Siddharthnagar 13.25 25.47 19.78 18.91 22.31 21.03 21.84 Badaun 18.88 12.50 21.65 18.84 18.52 8.61 13.03 Bahraich 8.47 26.44 12.97 13.58 6.25 17.05 13.46 Lakhimpur 20.80 30.56 24.66 24.10 25.49 21.74 23.02 Muzaffar Nagar 49.68 34.69 58.43 51.04 62.79 46.94 48.60 Balrampur 23.04 55.45 32.58 33.81 47.22 45.08 45.21 Pilibhit 13.43 13.89 12.73 13.04 14.00 6.98 8.95 J.P. Nagar 3.80 7.14 3.73 3.99 17.86 5.24 6.87 Moradabad 12.22 16.67 14.14 13.73 10.00 14.77 13.31 Saharanpur 16.22 25.00 18.89 18.98 100.00 21.15 21.58 Barabanki 45.69 53.13 52.59 49.58 67.86 54.85 56.23 Bijnore 23.64 24.62 25.50 24.29 46.67 38.30 38.55 Baghpat 27.27 29.91 27.11 27.67 66.67 27.39 27.62 Shravasti 39.89 60.20 52.67 50.23 66.67 33.62 35.69 Lucknow 51.60 43.59 37.79 46.61 100.00 53.60 53.49 Bareilly 28.95 47.06 39.52 36.87 33.33 30.97 32.76 Rampur 80.95 100.00 71.43 76.62 NA 76.82 76.43 Bulandshahar 2.84 5.26 4.42 4.14 6.25 2.67 4.00 Shahjahanpur 50.25 62.20 59.39 56.41 72.41 63.53 65.02 Average 26.76 31.70 28.44 28.25 26.96 31.85 30.97

Annexure 14: District-wise Literacy Rate (6 years & above) – Bihar MCDs (%) District Hindu Muslim SC & ST OBC GC* Total OBC GC* Total Araria 47.43 66.34 83.33 59.58 57.12 58.00 57.04 Bettiah 52.25 59.84 83.81 58.90 61.75 72.46 64.73 Darbhanga 50.00 56.16 77.09 55.70 53.84 62.23 58.78 Katihar 53.56 58.53 71.88 57.27 56.24 57.52 57.14 Kishanganj 46.15 67.38 56.25 58.44 55.72 55.03 55.34 Purniya 38.36 55.89 54.37 49.51 43.58 51.25 44.82 Sitamari 51.87 59.77 83.79 61.61 55.81 61.68 58.47 Average 49.34 60.00 78.82 57.68 54.10 59.09 55.87

Annexure 15: District-wise Dropouts Among 5-15 Age Group in Bihar MCDs (%) District Hindu Muslim SC & ST OBC GC* Total OBC GC* Total Araria 3.31 6.55 0.00 5.03 3.51 2.38 3.49 Bettiah 1.13 2.95 0.56 2.12 2.77 3.30 3.11 Darbhanga 1.80 4.67 0.00 3.05 3.21 6.63 5.11 Katihar 1.63 2.36 0.00 2.08 4.11 5.93 5.05 Kishanganj 0.71 3.76 0.00 2.51 1.59 2.84 2.13 Purniya 0.00 1.63 2.94 1.17 1.32 0.00 1.08 Sitamari 1.17 2.01 0.00 1.47 3.81 0.64 2.21 Average 1.49 3.29 0.42 2.43 2.59 3.77 3.06 *General category

91

Annexure 16: District-wise Enrolment Among 5-15 Age Group in Bihar MCDs (%) District Hindu Muslim SC & ST OBC GC* Total OBC GC* Total Araria 86.09 90.39 100.00 89.20 90.69 96.03 91.53 Bettiah 74.93 81.33 93.13 79.53 74.33 79.33 76.30 Darbhanga 67.57 79.40 92.98 75.20 73.40 77.55 75.71 Katihar 87.50 86.13 100.00 86.81 79.65 81.85 80.97 Kishanganj 77.30 78.40 100.00 78.21 78.61 76.06 77.52 Purniya 65.75 79.27 85.29 75.12 62.71 71.75 64.24 Sitamari 75.88 82.14 89.38 81.17 75.24 88.18 81.39 Average 75.58 82.62 91.10 80.66 76.38 80.60 77.96

Annexure 17: District-wise Educational Status of Matric and above – Bihar (%) District Hindu Muslim SC & ST OBC GC* Total OBC GC* Total Araria 8.58 20.79 32.00 17.61 10.05 7.17 9.49 Bettiah 9.14 11.79 29.95 13.21 5.91 15.09 8.88 Darbhanga 12.18 14.67 37.14 16.91 10.75 13.24 12.30 Katihar 8.75 10.19 17.39 9.96 6.18 8.20 7.34 Kishanganj 4.30 6.12 11.11 5.60 9.36 9.79 9.66 Purniya 5.46 14.45 12.50 11.80 10.83 13.53 11.36 Sitamari 7.20 14.34 35.71 17.57 10.20 9.07 9.49 Average 8.67 13.37 32.13 14.10 9.12 10.59 9.69

Annexure 18: District-Wise Average Family Size in Bihar MCDs Hindu Muslim SC & District ST OBC GC* All OBC GC* All Araria 5.2 5.7 5.3 5.4 6.3 5.6 6.2 Bettiah 5.6 5.9 5.8 5.8 6.1 6.3 6.1 Darbhanga 5.7 5.6 6.0 5.7 6.0 5.9 5.9 Katihar 5.5 5.6 4.4 5.5 6.1 5.9 6.0 Kishanganj 5.8 5.6 4.5 5.6 6.3 6.1 6.2 Purniya 5.1 5.4 4.8 5.2 6.0 5.3 5.8 Sitamari 5.7 5.8 5.9 5.8 6.1 6.1 6.1 Average 5.5 5.7 5.7 5.6 6.2 5.9 6.0

Annexure 19: District-wise Dependency Ratio in Bihar MCDs District Hindu Muslim SC & ST OBC GC* Total OBC GC* Total Araria 92 95 90 93 102 83 100 Bettiah 94 87 69 88 107 107 107 Darbhanga 91 89 62 87 111 86 96 Katihar 105 96 57 98 113 92 100 Kishanganj 102 92 50 95 102 96 99 Purniya 95 87 79 89 102 96 101 Sitamari 113 92 72 94 102 102 102 Average 97 91 70 91 105 94 100 *General category

92

Annexure 20: District-wise Secondary Sector Employment in Bihar MCDs (%) District Hindu Muslim SC & ST OBC GC* Total OBC GC* Total Araria 11.25 19.22 25.00 15.66 27.72 27.85 27.22 Bettiah 15.38 17.94 19.40 16.94 26.33 26.50 26.35 Darbhanga 33.99 26.04 20.48 29.22 43.21 44.83 44.16 Katihar 12.84 17.59 20.00 16.16 27.03 37.27 32.72 Kishanganj 20.26 22.94 33.33 21.94 27.53 25.78 26.79 Purniya 7.09 12.50 13.85 10.51 25.97 21.31 25.06 Sitamari 21.15 30.17 25.00 26.57 61.90 54.09 58.32 Average 18.46 20.98 21.15 19.98 30.62 34.63 32.01

Annexure 21: District-wise Service Sector Employment in Bihar MCDs (%) District Hindu Muslim SC & ST OBC GC* Total OBC GC* Total Araria 8.04 16.22 30.00 12.80 12.83 15.07 13.14 Bettiah 7.18 15.70 20.90 12.40 8.45 12.82 9.46 Darbhanga 18.42 24.95 33.73 22.69 22.84 20.91 21.70 Katihar 11.28 14.36 6.67 13.27 9.96 12.73 11.58 Kishanganj 5.73 12.90 22.22 9.90 16.10 14.73 15.61 Purniya 6.76 11.50 12.31 9.72 10.90 10.25 10.74 Sitamari 10.04 12.24 39.52 15.39 16.83 15.30 15.82 Average 10.24 15.55 28.20 14.30 13.34 14.91 13.90

Annexure 22: Workers’ Migration (%) in Bihar MCDs Hindu Muslim SC & ST OBC GC* Total OBC GC* Total Araria 8.89 9.76 8.11 9.35 12.34 10.10 12.11 Bettiah 10.55 10.61 12.86 10.79 13.62 11.38 13.02 Darbhanga 14.13 15.16 24.02 15.57 12.99 18.14 15.96 Katihar 7.36 9.02 5.56 8.44 9.40 16.18 13.15 Kishanganj 11.35 12.37 22.22 12.08 13.70 15.77 14.60 Purniya 14.59 14.30 18.40 14.72 15.11 11.48 14.41 Sitamari 8.38 11.46 16.23 11.32 17.60 18.28 17.86 Average 10.90 11.67 16.57 11.78 13.49 15.46 14.25

Annexure 23: Incidence of Indebtedness (%HH) in Bihar MCDs Hindu Muslim SC & ST OBC GC* Total OBC GC* Total Araria 30.30 44.19 28.57 37.74 41.86 58.65 44.74 Bettiah 54.01 53.75 50.00 53.53 44.66 40.21 43.58 Darbhanga 52.76 54.87 59.52 54.39 50.60 40.26 44.58 Katihar 33.04 41.95 57.14 39.44 42.98 37.54 39.85 Kishanganj 21.35 32.17 0.00 26.92 33.67 43.12 37.19 Purniya 40.68 50.58 53.85 47.15 59.20 54.03 58.49 Sitamari 52.35 56.41 46.84 53.69 49.41 48.48 48.55 Average 43.92 49.27 49.09 47.21 45.76 44.07 45.05

*General category

93

Annexure 24: District-wise In-house Drinking Water in Bihar MCDs (%) District Hindu Muslim SC & ST OBC GC* Total OBC GC* Total Araria 55.30 82.56 85.71 71.38 75.34 71.15 74.33 Bettiah 37.13 56.13 79.17 49.81 50.99 65.98 54.75 Darbhanga 23.12 37.61 69.05 34.26 46.99 59.74 54.41 Katihar 50.89 66.10 87.50 61.80 59.21 69.77 65.41 Kishanganj 56.18 83.90 75.00 72.04 73.75 77.98 75.55 Purniya 61.86 79.07 57.69 70.89 76.50 87.10 78.73 Sitamari 18.12 45.05 55.70 38.72 34.12 35.15 34.88 Average 39.96 60.90 66.97 53.38 65.07 66.82 65.70

Annexure 25: Literacy Rate (6 years & above) in West Bengal MCDs District Hindu Muslim- SC OBC GC* Total General & ST Burdwan 68.1 89.2 87.6 77.0 72.4 Birbhum 63.3 92.1 86.5 72.5 70.7 Coochbehar 71.4 78.9 72.1 71.7 59.8 Daksin Dinajpur 60.8 74.1 74.8 64.4 76.4 Haora 91.8 36.4 92.6 91.1 95.9 Malda 35.0 75.0 43.8 41.3 56.4 Murshidabad 83.4 83.8 77.4 79.2 67.8 Nadia 66.9 68.0 72.3 70.5 49.8 North_24prg 83.3 87.0 88.1 85.7 79.5 South_24prg 74.3 86.7 89.3 80.0 74.3 Uttar Dinajpur 65.0 62.5 70.6 69.0 53.4 Average 65.0 62.5 70.6 69.0 53.4

Annexure 26: Percentage with ‘Matric and Above’ Educational Status in West Bengal MCDs District Hindu Muslim- SC OBC GC* Total General & ST Burdwan 11.9 22.8 32.6 21.9 9.9 Birbhum 9.9 22.1 28.9 17.9 14.8 Coochbehar 11.2 20.0 21.4 14.2 6.9 Daksin Dinajpur 11.8 21.7 19.4 14.1 15.9 Haora 40.2 0.0 42.5 41.5 15.0 Malda 7.3 8.3 28.6 15.9 11.1 Murshidabad 18.7 35.1 24.0 23.3 12.5 Nadia 10.1 0.0 14.5 12.5 12.6 North_24prg 15.1 28.9 26.2 21.1 10.2 South_24prg 12.7 37.2 34.2 22.1 7.5 Uttar Dinajpur 19.2 20.0 18.6 18.8 8.3 Average 12.7 25.1 27.6 19.6 11.0

*General category

94

Annexure 27: Households with Pucca Houses in West Bengal MCDs (%) District Hindu Muslim- SC & OBC GC* Total General ST Burdwan 7.6 10.8 35.4 18.9 12.3 Birbhum 3.4 26.5 26.8 12.0 7.9 Coochbehar 1.0 0.0 6.6 2.5 1.3 Daksin 2.9 5.0 3.7 3.1 5.2 Dinajpur Haora 22.7 6.7 39.3 32.7 13.9 Malda 2.5 14.8 13.8 5.7 1.4 Murshidabad 8.0 21.9 35.6 18.8 19.0 Nadia 5.8 13.5 17.9 11.8 8.8 North_24prg 17.2 27.6 33.1 25.2 16.4 South_24prg 4.3 11.4 5.9 5.3 0.0 Uttar Dinajpur 13.9 22.2 26.3 18.7 8.9 Average 7.0 15.9 26.3 14.3 9.9

Annexure 28: Households with Electricity in West Bengal MCDs (%) District Hindu Muslim- SC OBC GC* Total General & ST Burdwan 30.9 45.9 67.9 46.5 37.0 Birbhum 15.6 55.9 55.4 30.4 28.0 Coochbehar 10.8 11.1 25.2 14.7 6.3 Daksin 14.2 20.0 39.3 20.0 33.1 Dinajpur Haora 72.2 60.0 87.1 81.2 65.9 Malda 16.7 51.9 43.1 24.7 19.3 Murshidabad 24.0 65.6 60.0 40.8 28.0 Nadia 24.2 51.4 47.7 36.6 23.3 North_24prg 44.4 48.3 71.1 57.2 49.2 South_24prg 34.0 50.0 47.4 39.5 30.4 Uttar Dinajpur 23.8 22.7 58.8 26.9 21.0 Average 25.7 45.4 59.7 38.8 30.3

Annexure 29: Households with In-House Access to Safe Drinking Water in West Bengal MCDs (%) District Hindu Muslim- SC OBC GC* Total General & ST Burdwan 20.6 29.7 47.6 31.9 19.0 Birbhum 10.4 20.6 31.2 17.4 8.8 Coochbehar 72.6 100.0 76.2 74.0 74.3 Daksin Dinajpur 39.7 45.0 46.7 41.4 31.6 Haora 17.5 53.3 38.2 31.5 24.7 Malda 7.9 33.3 56.9 19.5 29.6 Murshidabad 23.2 62.5 45.6 35.2 31.6 Nadia 63.9 62.2 69.8 66.5 51.4 North_24prg 54.0 62.1 65.7 60.0 60.8 South_24prg 16.6 16.7 15.4 16.2 13.6 Uttar Dinajpur 69.5 90.9 85.3 73.6 59.7 Average 37.9 52.0 50.3 43.1 37.8

*General category

95

Annexure 30: Households with In-house W.C. Toilet Facility in West Bengal MCDs (%) District Hindu Muslim - SC & ST OBC GC Total General Burdwan 43.4 32.4 61.3 49.9 45.5 Birbhum 7.7 29.4 29.9 15.9 13.4 Coochbehar 46.9 77.8 61.6 51.5 39.2 Daksin Dinajpur 11.8 40.0 54.1 22.1 12.3 Haora 51.5 60.0 77.8 68.3 67.6 Malda 6.3 51.9 35.4 15.7 13.4 Murshidabad 22.7 56.3 57.8 38.2 21.6 Nadia 65.7 89.2 74.8 71.4 44.8 North_24prg 77.4 82.8 86.6 82.1 79.4 South_24prg 44.4 61.1 56.4 49.4 37.4 Uttar Dinajpur 16.0 18.2 44.1 18.9 7.2 Average 34.5 51.0 64.6 46.1 33.5

Annexure 31: District-Wise Average Household Size in Assam MCDs District Hindu Muslim- General SC & ST OBC GC Total Total* Kamrup 5.60 5.67 5.56 5.61 5.58 Barpeta 5.19 4.64 5.51 5.26 5.92 Darrang 5.46 5.22 5.08 5.28 5.99 Marigaon 5.21 4.53 5.28 5.06 5.57 Kokrajhar 4.89 4.55 4.98 4.85 5.40 Bongaigaon 5.16 4.76 4.58 4.95 5.43 Dhubri 4.74 4.57 4.65 4.64 5.74 Nagaon 5.50 5.08 5.28 5.26 5.75 Gopalpara 4.83 4.77 4.47 4.74 5.73 Hailakandi 5.38 5.10 4.84 5.18 5.85 Cachar 4.83 4.93 4.92 4.88 5.03 N.C. Hills 4.83 4.88 5.90 4.88 NA Karimganj 4.63 4.93 4.88 4.80 6.26 Average 5.09 4.96 5.12 5.06 5.69 *Almost entirely General category except a small fraction of OBCs in Darrang, Hailakandi and Cachar.

Annexure 32: Sex Ratio in Assam MCDs (Females per 1000 Male Population) District Hindu Muslim- General SC & ST OBC GC Total Total*

Kamrup 859 890 876 872 929 Barpeta 1019 875 921 949 897 Darrang 924 948 936 933 938 Marigaon 876 869 943 885 864 Kokrajhar 958 886 850 932 903 Bongaigaon 983 942 732 944 937 Dhubri 971 908 755 914 937 Nagaon 945 903 836 906 909 Gopalpara 1030 1032 878 998 893 Hailakandi 825 752 873 810 814 Cachar 993 975 935 977 923 N.C. Hills 896 1108 879 902 NA Karimganj 867 942 866 895 908 Average 922 909 888 912 906 *Almost entirely General category except a small fraction of OBCs in Darrang, Hailakandi and Cachar.

96

Annexure 33: f Dependency Ratio* Across the MCDs in Assam District Hindu Muslim- SC OBC GC Total General & ST Kamrup 59 63 62 61 73 Barpeta 63 47 49 53 85 Darrang 55 61 59 57 89 Marigaon 57 39 70 54 95 Kokrajhar 59 65 78 63 97 Bongaigaon 81 58 49 69 88 Dhubri 83 73 41 73 90 Nagaon 70 65 53 64 97 Gopalpara 60 61 39 55 96 Hailakandi 74 53 51 62 71 Cachar 60 50 46 53 67 N.C. Hills 25 30 36 26 NA Karimganj 54 49 44 50 91 Total 55 57 54 55 87 *Percentage of Non-earning members to Earning members in the household.

Anne xure 34: Proportion of Children 6-10 Age Group Never Enrolled in School in Assam MCDs (%) District Hindu Muslim- SC & OBC GC Total General ST Kamrup 3.4 5.5 2.6 3.8 4.4 Barpeta 3.8 0.0 1.7 2.2 0.7 Darrang 0.8 1.4 2.4 1.5 3.6 Marigaon 0.4 1.3 0.0 0.5 0.0 Kokrajhar 10.0 21.5 9.9 11.4 18.4 Bongaigaon 3.4 3.8 0.0 3.3 4.2 Dhubri 0.9 0.0 0.0 0.3 2.5 Nagaon 0.3 2.4 0.7 1.3 2.7 Gopalpara 2.5 0.0 4.4 2.4 8.0 Hailakandi 1.1 2.8 3.8 2.2 2.3 Cachar 1.3 2.2 0.0 1.4 0.9 N.C. Hills 0.5 0.0 0.0 0.4 NA Karimganj 0.0 0.0 3.3 0.8 1.5 Average 2.5 2.9 2.6 2.6 3.9

Annexure 35: Proportion of School Dropouts in Assam MCDs(%) District Hindu Muslim- SC & OBC GC Total General ST Kamrup 9.2 4.7 4.8 6.8 10.4 Barpeta 5.8 6.2 3.9 5.0 3.2 Darrang 9.8 6.3 12.6 10.1 9.4 Marigaon 24.1 23.6 19.6 23.4 19.7 Kokrajhar 17.6 16.1 19.8 17.8 20.5 Bongaigaon 11.3 11.3 8.9 11.1 9.3 Dhubri 7.8 3.1 13.3 5.9 5.4 Nagaon 12.8 18.7 16.8 16.1 10.0 Gopalpara 14.4 9.0 11.5 12.9 8.8 Hailakandi 27.7 30.0 28.5 28.6 33.1 Cachar 4.7 5.2 11.6 6.1 6.6 N.C. Hills 22.7 7.9 14.3 21.3 NA Karimganj 35.9 26.2 24.2 29.5 20.9 Average 17.1 14.4 14.3 15.8 12.7

97

Annexure 36: roportion of Children Enrolled in Elementary Schools in Assam MCDs (%) District Hindu Muslim- SC & OBC GC Total General ST Kamrup 87.4 89.8 92.6 89.4 85.2 Barpeta 90.4 93.8 94.4 92.8 96.1 Darrang 89.3 92.3 85.0 88.4 87.0 Marigaon 75.5 75.2 80.4 76.1 80.3 Kokrajhar 72.3 62.4 70.2 70.8 61.1 Bongaigaon 85.4 84.9 91.1 85.6 86.4 Dhubri 91.3 96.9 86.7 93.8 92.1 Nagaon 86.8 78.9 82.5 82.6 87.4 Gopalpara 83.1 91.0 84.1 84.8 83.2 Hailakandi 71.2 67.2 67.7 69.3 64.6 Cachar 94.0 92.6 88.4 92.5 92.5 N.C. Hills 76.9 92.1 85.7 78.3 Karimganj 64.1 73.8 72.5 69.7 77.5 Average 80.4 82.7 83.1 81.5 83.4

Annexure 37: Proportion of Landless Households in Assam MCDs (%) District Hindu Muslim- SC & OBC GC Total General ST Kamrup 47.8 47.6 53.6 49.1 47.2 Barpeta 6.0 14.3 0.0 4.6 5.0 Darrang 7.5 11.5 6.4 8.3 11.2 Marigaon 7.5 11.5 6.4 8.3 11.2 Kokrajhar 6.1 2.7 10.7 6.1 11.2 Bongaigaon 1.8 1.7 3.4 2.0 6.7 Dhubri 48.6 48.6 85.0 52.2 58.0 Nagaon 50.0 31.1 38.5 39.0 36.1 Gopalpara 0.0 0.0 0.0 0.0 0.0 Hailakandi 49.4 54.1 48.1 50.7 32.3 Cachar 75.7 73.0 85.2 76.1 77.6 N.C. Hills 4.0 18.8 14.3 5.0 Karimganj 67.8 60.0 71.3 65.7 39.8 Average 23.0 36.3 29.5 27.9 29.4

Annexure 38: Share of Agriculture and Allied Activities in Total Employment in Assam MCDs (%) District Hindu Muslim- SC & OBC GC Total General ST Kamrup 75.2 75.1 68.2 73.4 69.9 Barpeta 31.6 45.7 26.7 31.0 51.2 Darrang 51.6 61.0 54.5 54.4 49.9 Marigaon 59.8 54.1 49.4 57.2 56.1 Kokrajhar 50.1 43.7 39.8 47.2 31.1 Bongaigaon 39.0 47.2 39.0 41.9 45.2 Dhubri 57.6 57.8 3.6 51.5 43.2 Nagaon 47.1 53.9 38.9 49.1 46.0 Gopalpara 36.7 37.7 34.0 36.2 38.6 Hailakandi 51.0 50.0 44.0 49.3 56.6 Cachar 28.3 26.2 11.5 24.4 26.4 N.C. Hills 69.1 48.5 44.0 67.3 NA Karimganj 19.9 20.1 6.0 17.2 21.4 Average 54.6 48.8 41.2 50.5 44.5

98

Annexure 39: Share of Secondary Sector in Total Employment in Assam MCDs (%) District Hindu Muslim - SC & OBC GC Total General ST Kamrup 8.7 11.6 17.3 11.8 13.0 Barpeta 28.6 5.7 12.6 17.5 21.5 Darrang 16.5 11.0 9.6 13.1 13.2 Marigaon 11.7 15.8 11.2 12.5 13.7 Kokrajhar 18.7 21.4 35.9 22.4 32.3 Bongaigaon 23.2 12.0 17.1 18.5 18.0 Dhubri 11.8 16.4 35.7 17.0 20.3 Nagaon 13.2 11.4 12.6 12.2 16.5 Gopalpara 29.5 23.4 13.6 24.9 28.0 Hailakandi 21.0 23.8 29.0 23.5 21.6 Cachar 37.7 18.6 19.5 26.2 35.1 N.C. Hills 13.2 6.1 14.0 13.0 Karimganj 28.6 19.5 27.7 24.8 26.3 Average 17.7 15.8 18.3 17.3 21.8

Annexure 40: Employment in Tertiary Sector in Assam MCDs (%) District Hindu Muslim - SC & OBC GC Total General ST Kamrup 16.1 13.3 14.5 14.9 17.1 Barpeta 39.8 48.6 60.7 51.5 27.3 Darrang 31.9 28.0 35.9 32.5 37.0 Marigaon 28.5 30.1 39.3 30.3 30.2 Kokrajhar 31.2 35.0 24.2 30.4 36.6 Bongaigaon 37.8 40.7 43.9 39.6 36.9 Dhubri 30.6 25.8 60.7 31.5 36.5 Nagaon 39.7 34.6 48.4 38.8 37.6 Gopalpara 33.8 39.0 52.4 38.9 33.4 Hailakandi 28.0 26.2 27.0 27.2 21.8 Cachar 34.0 55.2 69.0 49.4 38.5 N.C. Hills 17.8 45.5 42.0 19.7 100.0 Karimganj 51.6 60.4 66.3 58.1 52.3 Average 27.7 35.4 40.5 32.1 33.7

Annexure 41: Incidence of Household Indebtedness in Assam MCDs (%) District Hindu Muslim- SC & OBC GC Total General ST Kamrup 34.2 31.8 35.9 34.0 36.8 Barpeta 24.7 38.1 26.1 27.5 27.3 Darrang 18.8 15.8 15.6 17.7 41.8 Marigaon 18.8 15.8 15.6 17.7 41.8 Kokrajhar 13.8 17.2 16.1 14.6 27.5 Bongaigaon 17.6 16.5 12.9 16.8 15.3 Dhubri 5.6 12.8 0.0 9.0 14.6 Nagaon 10.6 9.8 21.9 12.3 19.4 Gopalpara 2.9 7.6 9.2 5.1 2.9 Hailakandi NA 1.6 NA 0.5 0.3 Cachar 4.0 6.1 6.6 5.3 4.6 N.C. Hills 0.5 NA 4.8 0.7 NA Karimganj 0.0 3.0 2.5 1.7 0.8 Average 13.3 16.0 21.7 15.7 19.7

99

Annexure 42: Share of Formal Institutional Sources in Household Debt in Assam MCDs (%) District Hindu Muslim - SC & OBC GC Total General ST Kamrup 25.7 32.6 38.1 30.8 39.8 Barpeta 36.4 50.0 45.5 43.7 20.7 Darrang 37.3 50.0 30.0 39.0 7.2 Marigaon 37.3 50.0 30.0 39.0 7.2 Kokrajhar 32.5 18.2 10.0 26.2 12.6 Bongaigaon 16.1 19.0 25.0 17.9 15.7 Dhubri NA 21.4 16.7 24.5 Nagaon 13.3 10.5 37.5 20.0 16.8 Gopalpara 50.0 40.0 14.3 33.3 35.7 Hailakandi NA NA NA NA 100.0 Cachar 42.9 50.0 100.0 57.1 43.5 N.C. Hills NA NA NA NA NA Karimganj - 100.0 NA 66.7 50.0 Average 27.0 31.4 38.4 31.3 20.6

Annexure 43: Proportion of Households with Access to PDS in Assam MCDs (%) District Hindu Muslim- SC & OBC GC Total General ST Kamrup 66.7 77.5 82.1 73.6 81.6 Barpeta 82.4 72.5 82.4 80.9 77.7 Darrang 53.1 67.3 60.9 57.6 44.4 Marigaon 53.1 67.3 60.9 57.6 44.4 Kokrajhar 85.2 87.7 95.2 87.0 89.3 Bongaigaon 84.2 84.3 87.1 84.5 80.4 Dhubri 83.3 79.8 90.0 82.1 76.6 Nagaon 75.9 62.4 86.3 71.3 73.7 Gopalpara 85.1 87.9 90.8 86.9 81.3 Hailakandi 50.0 42.6 53.2 48.3 47.8 Cachar 71.7 74.8 59.0 71.0 78.4 N.C. Hills 94.8 93.8 85.7 94.3 NA Karimganj 65.1 66.7 77.5 68.4 73.2 Average 76.3 72.6 77.3 75.5 73.5

Annexure 44: Households with Houses with Pucca Walls in Assam MCDs (%) District Hindu Muslim- SC & OBC GC Total General ST Kamrup 28.4 27.6 26.8 27.8 23.0 Barpeta 23.9 33.3 55.6 41.3 12.3 Darrang 7.0 7.7 8.1 7.5 8.9 Marigaon 19.5 27.0 29.7 22.7 10.3 Kokrajhar 9.8 5.2 17.7 10.4 3.2 Bongaigaon 16.5 22.0 38.7 20.7 17.7 Dhubri 2.8 0.0 5.0 1.5 5.4 Nagaon 22.7 25.3 28.8 25.0 18.6 Gopalpara 7.2 13.6 10.5 9.1 1.5 Hailakandi 38.9 27.9 35.4 34.6 27.3 Cachar 6.4 14.9 23.0 12.4 6.9 N.C. Hills 8.5 6.3 4.8 8.3 NA Karimganj 9.0 11.4 15.0 11.2 9.0 Average 7.3 8.9 14.8 9.2 5.0

100

Annexure 45: Households with Access to In-house Drinking Water in Assam MCDs (%) District Hindu Muslim- SC & OBC GC Total General ST Kamrup 61.3 72.4 54.4 62.7 65.6 Barpeta 81.5 73.8 87.4 83.3 78.4 Darrang 80.1 83.0 89.1 82.1 82.1 Marigaon 80.1 83.0 89.1 82.1 82.1 Kokrajhar 60.3 63.8 69.4 62.1 65.8 Bongaigaon 42.0 62.2 83.9 53.6 75.0 Dhubri 36.1 80.7 90.0 65.7 83.5 Nagaon 53.2 48.5 80.8 55.9 81.2 Gopalpara 34.6 48.5 68.4 44.6 59.5 Hailakandi 6.1 9.0 8.9 7.6 9.1 Cachar 10.4 11.0 8.2 10.3 10.1 N.C. Hills 40.0 56.3 42.9 40.7 NA Karimganj 16.4 14.1 32.5 19.1 9.9 Average 47.3 48.2 59.4 50.0 59.3

Annexure 46: Proportion of Households with In-house Toilet Facility in Assam MCDs (%) District Hindu Muslim- SC OBC GC Total General & ST Kamrup 38 35 34 36 39 Barpeta 35 29 45 39 27 Darrang 22 19 18 20 19 Marigaon 40 54 48 45 52 Kokrajhar 14 21 21 16 15 Bongaigaon 26 31 35 29 27 Dhubri 21 26 45 26 24 Nagaon 35 30 53 36 39 Gopalpara 65 59 62 63 41 Hailakandi 98 95 92 96 96 Cachar 83 95 98 90 94 N.C. Hills 92 100 95 93 NA Karimganj 99 99 96 98 98 Average 54 53 51 53 47

Annexure 47: Households with Electricity in Assam MCDs (%) District Hindu Muslim- SC OBC GC Total General & ST Kamrup 39 28 44 37 29 Barpeta 24 14 61 41 7 Darrang 18 14 18 17 16 Marigaon 14 39 33 22 15 Kokrajhar 31 21 19 28 13 Bongaigaon 15 15 29 16 12 Dhubri 1 15 55 14 11 Nagaon 17 25 42 25 15 Gopalpara 23 32 36 27 5 Hailakandi 29 29 24 28 23 Cachar 17 37 59 32 23 N.C. Hills 41 63 57 43 NA Karimganj 20 44 46 35 17 Average 25 28 39 29 15

101

References

Basant, Rakesh and Abusaleh Shariff (eds) (2010) Handbook of Muslims: Empirical and Policy Perspectives, Oxford University Press, New Delhi.

Desai, Sonalde and Veena Kulkarni (2010) “Unequal Playing Field: Socio -religious Inequalities in Educational Attainment” in Basant and Shariff (eds) op. cit.

GoI (2006) Social, Economic and Educational Status of the Muslim Community in India: A Report, Prime Minister’s High Level Committee, Cabinet Secretariat, Government of India, New Delhi, November.

GoI, Planning Commission (2008) Eleventh Five Year Plan 2007-2012, Vol. I, Planning Commission, New Delhi.

Hashim, S.R (2008) “Evaluation of Baseline Survey Report”.

Khalidi, Omar (2006) Muslims in Indian Economy, New Delhi, Three Essays Collective.

Krishnan, P.S. (2010) “Understanding the Backward Classes of Muslim Society”, Economic and Political Weekly, Vol. XLV No. 34, August 21, pp. 46-56.

Kundu, Amitabh (2008) “Comments on Baseline Survey Reports for Nine Minority Concentration Districts”, Communication to the ICSSR, New Delhi.

Robinson, R (2007) “Indian Muslims: A Varied Dimension of Diversity”, Economic and Political Weekly, Vol. XLII, No. 10, March 11-16, pp. 839-842.

Saberwal, S (2010) “On the making of Muslims in India Historically” in Basant, and Shariff (eds) op. cit.

Shah, Ghanashyam (2007) “The Condition of Muslims”, Economic and Political Weekly, Vol. XLII, No. 10, March 11-16, pp. 836-839.

Wilkinson, Steven (2007) “A Comment on the Analysis in Sachar Report”, Economic and Political Weekly, Vol. XLII, No. 10, March 11-16, pp. 832-836.

102